Cardiovascular-oncogenic gene crosstalk in breast cancer: Survival, prognosis and therapeutic strategies

Abstract

Cardiovascular disorders (CVDs) are the leading cause of morbidity and mortality globally, followed by the cancer. Cardio-oncology research focuses on the cardiovascular complications during cancer therapies, common genes and molecular pathways associated with both diseases, and also the influence of cardiovascular genes in cancer prognosis and survival. The review highlighted the association between cardiovascular-related genes in breast cancer prognosis and survival outcomes. Cardiovascular and oncogenic gene networks in breast cancer survival, progression, and therapeutic strategies have been discussed. Many pro-inflammatory cytokines, such as tumor necrosis factor-α, interleukin-1β, interleukin-6, and transforming growth factor-β, released from malignant breast tumor cells and the tumor microenvironment, contribute to endothelial dysfunction, atherosclerosis, and various cardiovascular diseases. Different machine learning models have been developed to predict the CVD risk in breast cancer survival patients. Understanding crosstalk between cardiovascular-oncogenic gene networks and their association with common molecular pathways and signaling will be helpful for cancer therapeutics and a precision-medicine approach. In the future, breast cancer survival prediction models can be developed based on the differential expressed CVD genes in breast cancer patients.

Key Words: Cardio-oncology; Cardiovascular disorders; Cardiotoxicity; Inflammatory cytokines; Cell signaling; Breast cancer; Machine learning

Core Tip: The review based on cardio-oncology highlights the cardiovascular diseases (CVDs) and breast cancer associated gene network analysis, with significance of CVDs associated genes in breast cancer prognosis and therapeutics. Inflammatory cytokines and cellular signaling pathways interconnects both the diseases and increased cardiovascular risk in breast cancer patients. The review will be helpful to understand interconnection between these diseases and prediction of breast cancer survival based on differential expression of CVDs genes in future.

INTRODUCTION

Cancer and cardiovascular disease (CVD) represent two major causes of global morbidity and mortality and increasingly coexist as interconnected disorders rather than independent pathologies. Beyond shared environmental and clinical risk factors, emerging evidence suggests that cancer and CVD are linked through overlapping molecular mechanisms, including chronic inflammation, oxidative stress, clonal hematopoiesis, and dysregulated DNA damage response pathways. Breast cancer is a malignant condition where breast tissues start proliferating abnormally, and the breast tumor cells migrate to the surrounding tissues and other organs of the body. Breast cancer mainly occurs in the ducts (ductal carcinoma) and lobular parts (lobular carcinoma)[1,2]. Breast cancer remains a major global health concern, with approximately 2.4 million new cases and 694000 deaths estimated worldwide in 2024. Despite advances in screening and early diagnosis, treatment has significantly improved patient outcomes, yet survival remains uneven across socioeconomic groups. The global median five-year net survival is estimated at 77.8%, with rates varying from 41.9% in low-income countries to 87.3% in high-income countries[3], 24% of female cancer deaths arise from breast cancer, followed by cervical cancer. Breast cancer prognosis is influenced by pathways regulating cardiovascular homeostasis, including genes that control DNA damage, redox balance, and cell survival. This is because treatment of breast cancer can injure the cardiac tissue; therefore, any variation in cardiovascular-related genes can alter cancer outcomes and mortality risk[2,4]. There are common traditional risk factors for breast cancer and CVDs, such as diet, age, body mass index, tobacco use, and genetic factors[2]. Traditionally, the field of cardio-oncology has focused on the cardiotoxicity of anti-tumor therapies, such as chemotherapy-induced heart failure (HF) and radiotherapy-related valvular disease[5-7]. However, emerging evidence has ushered in the field of “reverse cardio-oncology”, which investigates how cardiovascular conditions like myocardial infarction and HF can actively accelerate tumor growth and metastasis[8]. This interaction is driven by a “multiple strike” theory, where common risk factors, genetic predispositions, and the systemic effects of a failing heart converge to exacerbate both diseases[9]. Shared modifiable risk factors like obesity, diabetes, hypertension, and smoking continue to underpin the epidemiological association between CVD and breast cancer[10-12]. Inflammation is a central player in this crosstalk; chronic systemic inflammation, distinct from acute responses, creates an immunosuppressive environment that promotes cancer cell proliferation, survival, and metastasis, while simultaneously driving atherosclerosis and vascular injury[13-15]. Oxidative stress driven by reactive oxygen species further bridges these diseases. At the same time, essential for normal cardiac function at low levels, increased level of reactive oxygen species causes mitochondrial dysfunction and DNA damage, which are hallmarks of both myocardial injury and tumorigenesis[16,17].

Research has documented that shared genetic background can predispose patients to CVDs, which can alter the risk of cancer relapse and survival[2,18]. Several CVD-associated genes also affect breast cancer proliferation, progression, and survival, thus influencing cancer outcomes. Cancer therapies also modulate the expression of various CVD genes, therefore linking them to cardiovascular disorders. Vascular endothelial growth factor-A, endothelial nitric oxide synthase, and angiopoietin-2, which are involved in angiogenesis and vascular remodeling, affect the tumor angiogenesis and invasiveness. Similarly, various cytokines, such as interleukin-6 (IL-6) and tumor necrosis factor (TNF), and signaling molecules involved in endothelial dysfunction and inflammation affect tumor progression and therapy resistance in breast cancer. Various oxidative stress and redox signaling genes (SOD, IRS1) play essential roles in CVDs, are also involved in tumor growth signaling, and affect therapeutic outcomes. Modulation of various genes during cancer therapy is linked to cardiotoxicity as well. Thus, CVD genes are associated with multiple outcomes of breast cancer progression and survival; vice versa, cancer therapies are also connected with genes that affect cardiotoxicity and cardiac functions[19-21].

CVD remains the foremost cause of mortality worldwide, affecting both the general population and individuals who have survived after breast cancer[22-25]. Evidence indicates that breast cancer patients face a substantially elevated risk of cardiovascular complications, with approximately a threefold increase in atherosclerotic CVD and one point five-fold-higher likelihood of developing HF compared to those without cancer[23,25]. As advances in cancer diagnosis and treatment continue to improve survival rates, the population of cancer survivors has steadily grown. Consequently, there is an increasing prevalence of non-cancer-related comorbidities, particularly cardiovascular conditions, which contribute significantly to long-term health outcomes in this population[22,24]. As survivorship increases, treatment-related cardiotoxicity, particularly associated with anthracyclines and trastuzumab, has emerged as an important clinical concern. Severe cardiotoxicity has been reported in approximately 3% of patients receiving trastuzumab-based therapy, underscoring the growing importance of cardio-oncology and the need to understand the molecular links between breast cancer and cardiovascular toxicity[26]. Collectively, these findings highlight the importance of investigating cardiovascular and oncogenic gene interactions as potential determinants of prognosis, survival, and therapeutic vulnerability in breast cancer[27].

Earlier reviews on cardio-oncology focused mainly on the cardiovascular complications after breast cancer therapies, few reviews discussed the association of cardiovascular and breast cancer-associated gene interaction, but no comprehensive literature about cardiovascular-oncogenic gene interaction in breast cancer survival outcomes. The present review also discussed the common inflammatory cytokines in breast cancer and cardiovascular complications. Lastly, it summarizes the influence of cardiovascular-associated genes on breast cancer outcomes. The review opens new windows for the use of machine-learning survival models for breast cancer prognosis based on the expression of cardiovascular-related genes. The review provides a comprehensive perspective on cardiovascular-oncogenic gene crosstalk in breast cancer and with direction of personalized therapeutic strategies.

The current review highlighted molecular crosstalk between CVDs and oncogenic gene networks in breast cancer prognosis, survival, and therapeutics. Cellular signaling pathways and inflammatory cytokines serve as the hub connecting these diseases. Understanding these interconnections will further help us develop and apply machine learning models that leverage differential expression of cardiovascular genes to predict breast cancer survival and therapeutic outcomes.

CARDIOVASCULAR AND ONCOGENIC GENE INTERACTIONS IN BREAST CANCER OUTCOMES

Recent advances in genomics have improved our understanding of the genetic mechanisms shared between cancer and CVDs. Several studies have reported that certain mutations contribute to the progression of both disorders. Gene network analyses identified Janus kinase 2 (JAK2), titin (TTN), and Tet methylcytosine dioxygenase 2 (TET2) as important molecular links between cancer and cardiovascular complications. Alterations in these genes have been associated with diseases including peripartum cardiomyopathy, breast cancer, clonal hematopoiesis of indeterminate potential (clonal hematopoiesis of indeterminate potential), and coronary artery disease[27]. In general, these shared genetic changes are mainly involved in three major biological processes: Inflammatory signaling, metabolic regulation, and cellular proliferation. Dysregulation of these pathways plays a crucial role in cancer initiation and progression, while also contributing to cardiovascular pathology.

JAK2 plays an important role in CVD by promoting inflammation, blood clot formation, and vascular damage. The JAK2V617F mutation continuously activates the JAK/signal transducer and activator of transcription signaling pathway, leading to excessive production and activation of blood cells, including platelets and white blood cells. As a result, patients have a higher risk of cardiovascular complications, including heart attack, stroke, and thrombosis. The study also shows that JAK2-mutant platelets and immune cells become more inflammatory and prone to clot formation, thereby promoting vascular injury and atherosclerosis. In addition, abnormal JAK2 signaling contributes to endothelial dysfunction and chronic inflammation, further worsening CVD. Abnormal activation of JAK2 is a major factor linking inflammation, thrombosis, and cardiovascular complications[28]. JAK2 also plays a role in breast cancer development. Abnormal activation of JAK2 signaling may contribute to the development of resistance to targeted therapies in breast cancer. Studies have further shown that JAK2 supports the self-renewal capacity of breast cancer stem cells by interacting with inflammatory mediators such as IL-6. Moreover, the combined effect of JAK2 with IL-6 and IL-8 has been reported to promote the growth and aggressive behavior of triple-negative breast cancer, highlighting its important role in tumor progression[29].

TTN is important for maintaining the structure, elasticity, and contraction of heart muscle cells. Mutations in the TTN gene, especially TTN truncating variants, are a major cause of dilated cardiomyopathy. These mutations impair sarcomere function, leading to reduced heart contractility, ventricular dilation, arrhythmias, and HF. TTN also acts as a mechanosensor, helping the heart respond to mechanical stress. Abnormal TTN outcomes that range from mild symptoms to severe heart disease and sudden cardiac death[30]. Recent studies suggest that changes in the TTN gene also play a role in the progression of breast cancer, especially triple-negative breast cancer. TTN inactivation has been linked with increased tumor growth, metastatic behavior, and poor response to treatment. It may also help create a tumor environment that weakens the body’s immune response against cancer. These findings indicate that TTN could be an important factor in breast cancer progression and patient outcome[31].

TET2 plays a protective role in CVD by regulating inflammation and preventing adverse cardiac remodeling. Loss of TET2 function was associated with increased inflammation, elevated IL-1β production, cardiac fibrosis, hypertrophy, and worsening HF. TET2 deficiency also promotes clonal hematopoiesis and the expansion of pro-inflammatory immune cells, thereby accelerating cardiovascular damage. Inhibition of the NOD-, LRR- and pyrin domain-containing protein 3 inflammasome reduced these inflammatory effects, indicating that TET2 normally helps maintain cardiovascular health by suppressing excessive inflammatory signaling[32]. TET2 plays a tumor-suppressive role in breast cancer. Some studies suggest that TET2 suppresses breast cancer progression by controlling epigenetic changes and regulating genes involved in tumor growth. Lower TET2 expression may be associated with more aggressive breast cancer, whereas increased TET2 activity reduced cancer cells ability to migrate and grow. The research also showed that TET2 can inhibit cancer-promoting pathways, particularly MYC signaling, and increase breast cancer cells sensitivity to stress-induced cell death, ultimately limiting tumor development[33].

G protein-coupled receptor kinase 4 (GRK4) has been implicated in both cardiovascular and cancer-related conditions, including hypertension and breast cancer. In hypertension, GRK4 regulates blood pressure by modulating G protein-coupled receptor (GPCR) signaling pathways involved in renal and vascular function[34]. In breast cancer, increased GRK4 expression has been associated with activation of β-arrestin-dependent mitogen-activated protein kinase signaling, suggesting a putative role in tumor development and progression[35].

AMP-activated protein kinase (AMPK) is a major regulator of cellular energy homeostasis and has been shown to have protective roles in CVD. Activation of AMPK mitigates oxidative stress[36] and inflammation[37] by suppressing reactive oxygen species production and inhibiting processes associated with atherosclerosis, including immune cell adhesion[38], foam cell formation[39], and vascular smooth muscle cell (VSMC) proliferation[40]. In addition to its cardiovascular benefits, AMPK also exhibits anti-cancer activity. Activation of AMPK has been reported to suppress breast cancer[41] by modulating signaling pathways such as phosphoinositide 3-kinase; mechanistic target of rapamycin, and tumor protein p53, which regulate proliferation, survival, and cell cycle progression[40,42].

Peroxisome proliferator-activated receptor gamma (PPAR-γ) is highly recognized for its role in glucose metabolism and insulin sensitivity. However, its biological functions extend beyond metabolic regulation and include important roles in inflammation, cardiovascular homeostasis, and cancer-associated signaling pathways[37]. Activation of PPAR-γ has been shown to exert protective effects against atherosclerosis[43,44] by enhancing endothelial function and suppressing key inflammatory processes. These include the reduction of pro-inflammatory cytokine production, inhibition of foam cell formation, and limitation of VSMCs[37,45,46]. In addition, PPAR-γ contributes to blood pressure regulation by modulating angiotensin II-dependent signaling pathways[45,47]. Beyond cardiovascular physiology, PPAR-γ is expressed in a variety of solid tumors, including breast cancer[37]. In these contexts, it generally acts as a tumor-suppressive factor by limiting cellular expansion, inhibiting cellular proliferation and angiogenesis, and promoting cellular differentiation[48].

The Wnt/β-catenin signaling pathway is a key regulator of cellular processes, including proliferation, migration, differentiation, and survival[49]. In this pathway, binding of Wnt proteins to Frizzled receptors and low-density-lipoprotein-receptor-related-protein 5/6 co-receptors stabilizes β-catenin, enabling its translocation into the nucleus where it activates T-cell-factor/Lymphoid-enhancer-binding-factor-dependent genes associated with cell growth and survival[50]. Dysregulated Wnt signaling has been implicated in the development of both cardiovascular disorders and cancer. In CVD, abnormal pathway activation contributes to endothelial dysfunction, inflammation, vascular calcification, monocyte adhesion, and proliferation of VSMCs[51-56]. Defective low-density-lipoprotein-receptor-related-protein 6-T-cell-factor 7 L2 signaling further promotes vascular remodeling and neointimal formation[57]. Many studies have reported increased activation of the Wnt/β-catenin signaling pathway in breast cancer[58]. Elevated β-catenin expression has been observed in nearly 60% of breast cancer cases, suggesting a significant involvement of this pathway in tumor progression[59]. Higher β-catenin levels were also associated with increased expression of the Wnt downstream target cyclin D1, which promotes cell cycle progression and uncontrolled cellular proliferation. Clinically, enhanced β-catenin activity has been linked with unfavorable patient outcomes and poor prognosis[59]. Moreover, abnormal expression of multiple Wnt pathway components has been identified at both the transcriptional and translational levels[59], which further suggests that dysregulated Wnt signaling may contribute to breast cancer development and aggressiveness. The roles of the genes discussed above in breast cancer and CVD are summarized in Table 1.

Table 1 Genes associated with breast cancer and cardiovascular diseases.

Gene name	Role in breast cancer	Role in cardiovascular disease
JAK2	JAK2 promotes triple-negative breast cancer progression through IL-6/IL-8 signaling[29]	Promoting inflammation, blood clot formation, and vascular damage[28]
TTN	Inactivation promotes tumor progression, metastasis, immune evasion, and poor prognosis[31]	Abnormal function of this gene impairs cardiac remodeling, leading to cardiomyopathy and sudden cardiac death[30]
TET2	Low TET2 promotes aggressive breast cancer, whereas high TET2 inhibits MYC signaling, tumor growth, migration, and enhances stress-induced cell death[33]	Plays a protective role in cardiovascular disease by regulating inflammation and preventing adverse cardiac remodeling[32]
GRK4	Promotes breast cancer progression via β-arrestin-dependent mitogen-activated protein kinase signaling[35]	Regulates blood pressure via GPCR signaling[34]
AMPK	AMPK suppresses breast cancer by inhibiting PI3K/mTOR and regulating p53 signaling[40-42]	AMPK activation suppresses reactive oxygen species, oxidative stress, inflammation, and atherosclerosis-related processes[36-40]
PPAR-γ	PPAR-γ acts as a tumor-suppressive factor by limiting cellular expansion, inhibiting cellular proliferation and angiogenesis, and promoting cellular differentiation[48]	PPAR-γ activation improves endothelial function and protects against atherosclerosis[43,44]
Wnt/β-catenin	Increased β-catenin activity promotes cyclin D1-mediated proliferation, tumor progression, and aggressiveness, and is associated with poor prognosis[59]	Wnt/β-catenin dysregulation promotes endothelial dysfunction, inflammation, vascular calcification, monocyte adhesion, vascular smooth muscle cell proliferation, vascular remodeling, and neointimal formation[51-56]

JAK2: Janus kinase 2; TTN: Titin; TET2: Tet methylcytosine dioxygenase 2; GRK4: G protein-coupled receptor kinase 4; AMPK: AMP-activated protein kinase; PPAR-γ: Peroxisome proliferator-activated receptor gamma; Wnt: Wingless-related integration site; IL: Interleukin; GPCR: G protein-coupled receptor; PI3K: Phosphoinositide 3-kinase; mTOR: Mechanistic target of rapamycin; p53: Tumor protein p53.

The molecular alterations identified in this context should be interpreted as interconnected components of broader biological networks rather than as independent gene-specific abnormalities. Although JAK2, TET2, TTN, GRK4, AMPK, PPAR-γ, and the Wnt/β-catenin pathway have distinct molecular functions, their biological effects may converge on common processes, including intracellular signaling, epigenetic regulation, metabolic homeostasis, inflammation, and tissue remodeling, and this influences the disease initiation, progression, and tissue responses[60-64]. JAK2-dependent cytokine signaling and Wnt/β-catenin activity regulate key cellular processes such as proliferation, survival, differentiation, and tissue remodeling, while GRK4 influences the regulation and duration of GPCR-mediated signaling[60,61]. TET2 adds an epigenetic dimension by regulating DNA demethylation and gene-expression programs involved in cellular identity and differentiation, potentially shaping how cells respond to abnormal signaling[62]. Similarly, AMPK and PPAR-γ link cellular energy metabolism to stress responses, glucose and lipid regulation, and inflammation, thereby providing a mechanistic link between metabolic imbalance and chronic inflammatory signaling[63,64].

In contrast, TTN has a primarily structural role in maintaining sarcomere organization and tissue integrity. Its biological significance is therefore likely to depend on the specific genetic alteration, affected tissue, and surrounding molecular environment rather than on direct involvement in the signaling pathways described above[65]. The convergence of these processes suggests that disease phenotypes may arise from interactions among signaling, metabolic, inflammatory, epigenetic, and structural mechanisms rather than from individual molecular alterations alone. This pathway-oriented perspective may therefore improve the biological interpretation of molecular findings. It may contribute to more refined molecular classification, risk assessment, and the identification of therapeutic strategies targeting shared metabolic, inflammatory, epigenetic, or signaling dysregulation[60-64]. The interplay between oncogenic and cardiovascular-associated genes and cellular signaling affects breast cancer progression and development.

INFLAMMATORY CYTOKINES AS A LINK BETWEEN BREAST CANCER AND CVD

Several risk factors are common to both malignancies and CVDs, including obesity, smoking, and chronic inflammation[5]. However, epidemiological evidence suggests that individuals diagnosed with breast cancer exhibit a higher likelihood of developing myocardial infarction compared to those without cancer[66]. This increased risk indicates that, beyond shared risk factors, breast cancer itself may contribute to ischemic alterations in cardiac tissue, thereby elevating the incidence of cardiovascular events. Tumor development triggers systemic immune responses, leading to the release of multiple pro-inflammatory mediators, including TNF-α, IL-1β, IL-6, and transforming growth factor-β (TGF-β)[67,68]. These cytokines can impair endothelial cell integrity and function, particularly in coronary vessels, which are highly exposed due to their rich perfusion. As a result, these inflammatory processes may promote vascular injury and accelerate the development of ischemic heart disease in individuals with breast cancer. TNF-α is a pleiotropic pro-inflammatory cytokine predominantly secreted by activated macrophages and malignant cells with additional contributions from fibroblasts, T lymphocytes, and natural killer cells. This coordinated cellular output facilitates its accumulation within the tumor microenvironment, where it exerts significant biological effects. Accumulating evidence indicates that TNF-α expression is substantially elevated in breast cancer tissues relative to non-malignant breast counterparts and stromal elements representing a major source of its production[69]. Mechanistically, TNF-α has been shown to enhance tumor cell proliferation and promote metastatic dissemination to distant organs[70,71]. Further clinical evidence indicates that circulating TNF-α levels in patients with breast cancer are positively associated with tumor burden, tumor-nodes-metastasis classification, and lymph node involvement[72,73].

Beyond its oncogenic implications, TNF-α also plays a pivotal role in cardiovascular pathology, particularly in the initiation and progression of coronary artery disease. Experimental findings suggest that TNF-α can directly injure vascular endothelial cells, thereby increasing endothelial permeability. This dysfunction facilitates lipid infiltration and deposition within the arterial wall, thereby accelerating the formation of atherosclerotic plaques in the coronary arteries[74]. TNF-α further amplifies inflammatory signaling and promotes pathological alterations, including clot formation, vascular constriction, and excessive growth of VSMCs. This increases susceptibility to ischemic heart disease and myocardial infarction[75]. In addition, TNF-α disrupts endothelial integrity by diminishing nitric oxide availability, a critical regulator of vascular contractile state. This reduction contributes to endothelial dysfunction, impaired coronary perfusion, and an elevated likelihood of ischemic events[76].

IL-1β is a key endogenous mediator released by leukocytes that functions as a potent pro-inflammatory cytokine, regulating immune and inflammatory processes[77]. Elevated levels of IL-1β are commonly detected within the immune microenvironment of diverse solid tumors, where it is predominantly secreted by immune cells, stromal fibroblasts, and malignant cells[78]. Increased circulating IL-1β has also been reported in patients with breast cancer[79], and its abundance is strongly linked to poorer clinical outcomes[80]. In luminal subtypes of breast cancer, IL-1β enhances IL-6 secretion via the nuclear factor kappa-light-chain-enhancer of activated B cells signaling pathway, thereby supporting tumor progression and a more aggressive phenotype[81]. In cardiovascular disorders, IL-1β is a key mediator of vascular inflammation by acting on endothelial cells. It triggers a potent inflammatory response by activating endothelial cells and upregulating pro-inflammatory cytokines and chemokines[82]. Moreover, IL-1β promotes the surface expression of adhesion molecules, including intercellular adhesion molecule-1, vascular cell adhesion molecule-1, and E-selectin on endothelial cells[83]. These molecules play a pivotal role in attracting circulating leukocytes, facilitating their rolling along the endothelium, firm adhesion, and subsequent migration into inflamed tissues. Intensified crosstalk between leukocytes and endothelial cells at sites of vascular inflammation aggravates tissue injury, disrupts endothelial homeostasis, and accelerates the development of cardiovascular disorders such as atherosclerosis and ischemia-reperfusion impairment. Moreover, this pro-inflammatory environment may further drive the atherogenic process by enhancing the expression of the purinergic receptor P2Y2, a key modulator of vascular signaling pathways[84]. Increased P2Y2 activity promotes the proliferation and migration of VSMCs. VSMCs drive structural changes in the vessel wall, promote neointima formation, and weaken plaque stability. These factors, when combined, increase the likelihood of arterial narrowing and unfavorable cardiovascular events in advanced atherosclerotic disease[85].

IL-6 is a pleiotropic cytokine and adipokine that exerts complex, context-dependent effects in both cancer development and inflammatory processes[86]. It is predominantly secreted by non-malignant cells, including monocytes, macrophages, T and B lymphocytes, fibroblasts, endothelial cells, and adipocytes[87], although breast tumor cells themselves can also produce IL-6[88]. Elevated circulating levels of IL-6 have been consistently correlated with unfavorable clinical outcomes in breast cancer[89]. Beyond its contribution to tumor initiation and progression, IL-6 plays a central role in systemic inflammation and is actively involved in the pathophysiology of atherosclerosis. Transcriptomic and pathway analyses have further demonstrated that IL-6-mediated signaling is linked to a range of cardiovascular complications arising from atherosclerotic lesions, including myocardial infarction and peripheral arterial disease[90].

Breast carcinoma cells can secrete substantial amounts of TGF-β, a key regulatory cytokine with multifaceted roles in cancer biology[68]. In breast malignancy, TGF-β significantly influences disease progression by facilitating epithelial-to-mesenchymal transition. This process enhances cellular motility and invasiveness, thereby promoting metastatic dissemination[91]. Moreover, TGF-β contributes to immune escape by attenuating anti-tumor immune responses, which supports tumor persistence and growth[92]. In addition to its oncogenic functions, elevated TGF-β levels in individuals with breast cancer may adversely affect cardiovascular health, particularly in relation to ischemic heart disease. TGF-β is known to drive cardiac fibrosis by stimulating fibroblast activation and increasing the accumulation of extracellular matrix components following ischemic injury[93]. Sustained activation of this pathway in cardiac tissue can result in pathological myocardial remodeling, ultimately elevating the likelihood of HF development[94]. Cardiovascular-oncogenic genes affect the expression of various cytokines (Figure 1). The roles of the cytokines discussed above in breast cancer and CVDs are summarized in Table 2.

Figure 1 Effects of cardiovascular-oncogenic genes on the expression of associated cytokines in breast cancer and cardiovascular disorders. The figure illustrates the regulatory network linking cardiovascular-oncogenic genes (Janus kinase 2, titin, Tet methylcytosine dioxygenase 2, G protein-coupled receptor kinase 4, AMP-activated protein kinase, peroxisome proliferator-activated receptor gamma, and wingless-related integration site/β-catenin) with key inflammatory and pro-fibrotic cytokines [tumor necrosis factor-α, interleukin-6 (IL-6), IL-1β, and transforming growth factor-β]. Solid arrows indicate positive regulatory interactions or activation, whereas blunt-ended lines indicate inhibitory interactions. Elevated expression of tumor necrosis factor-α, IL-6, and IL-1β contributes to a pro-inflammatory tumor microenvironment and vascular dysfunction, while transforming growth factor-β promotes epithelial-mesenchymal transition, tissue fibrosis, immune suppression, and extracellular matrix deposition. Collectively, these molecular interactions drive adverse disease outcomes, including breast cancer progression (tumor growth, invasion and metastasis, therapy resistance, and poor prognosis) and cardiovascular disease (atherosclerosis, myocardial infarction, hypertension, heart failure, and arrhythmias). JAK2: Janus kinase 2; TTN: Titin; TET2: Tet methylcytosine dioxygenase 2; GRK4: G protein-coupled receptor kinase 4; AMPK: AMP-activated protein kinase; PPAR-γ: Peroxisome proliferator-activated receptor gamma; Wnt: Wingless-related integration site; TNF-α: Tumor necrosis factor alpha; IL-6: Interleukin-6; IL-1β: Interleukin-1β; TGF-β: Transforming growth factor-β.

Table 2 Cytokines associated with breast cancer and cardiovascular diseases.

Cytokine	Role in breast cancer	Role in cardiovascular disease
TNF-α	TNF-α promotes breast cancer progression by enhancing tumor growth, metastasis, and inflammation, and its elevated level is associated with poor clinical outcomes[70,71]	TNF-α damages vascular endothelial cells, increasing endothelial permeability, lipid deposition, inflammation, thrombosis, and vascular smooth muscle cell proliferation, thereby promoting atherosclerosis and increasing the risk of ischemic heart disease and MI[74,75]
IL-1β	IL-1β induces IL-6 via nuclear factor kappa-light-chain-enhancer of activated B cells, promoting breast cancer progression and aggressiveness[81]	IL-1β increases endothelial adhesion molecules, promoting leukocyte recruitment and vascular inflammation. This leads to endothelial dysfunction and accelerates atherosclerosis[83,84]
IL-6	Elevated IL-6 levels correlated with unfavorable clinical outcomes in breast cancer[89]	IL-6 induces systemic inflammation and atherosclerosis, contributing to cardiovascular complications such as myocardial infarction and peripheral arterial disease[90]
TGF-β	TGF-β promotes epithelial-to-mesenchymal transition, thereby enhancing invasion, metastasis, and immune evasion, thereby supporting breast cancer progression[91,92]	Elevated TGF-β promotes cardiac fibrosis and pathological myocardial remodeling after ischemic injury, increasing the risk of ischemic heart disease and heart failure[93,94]

TNF-α: Tumor necrosis factor-alpha; IL-1β: Interleukin-1β; IL-6: Interleukin-6; TGF-β: Transforming growth factor-beta; MI: Myocardial infarction.

CARDIOVASCULAR-RELATED GENES INFLUENCING BREAST CANCER SURVIVAL AND PROGNOSIS

Many molecular and biological pathways, viz, inflammation, oxidative stress, angiogenesis, and metabolic regulation, interconnect breast cancer and cardiovascular disorders. Many genes that are involved in CVDs are also associated with breast cancer prognosis, progression, and survival. Angiogenesis and vascular regulation-associated genes are essential in tumor growth and proliferation. Several genes, including members of the vascular endothelial growth factor family, their receptors (vascular endothelial growth factor receptors), and fibroblast growth factors, play a central role in angiogenesis. Increased angiogenic signaling results in increased vasculature at the tumor, facilitates metastasis, and is associated with poor prognosis. Thus, angiogenesis-associated genes that regulate blood vessel formation are critical for heart function and tumor growth, serving as potential prognostic markers in breast cancer[95-97]. Oxidative stress-related genes, such as thioredoxin and superoxide dismutase 2, play a cardioprotective role by balancing the redox environment; their overexpression is linked to poor survival in breast cancer patients. This is an example of how cardioprotective genes can confer a poor cancer prognosis when overexpressed[98,99].

Breast cancer susceptibility gene 1/2 (BRCA1/2), known genetic risk factor of breast cancer, and in vivo and human studies suggest that BRCA1/2 deficiency is associated with CVDs such as ischemic heart disease, atherosclerosis, and chemotherapy-related cardiac dysfunction[100], which is most likely mediated through oxidative stress and altered nuclear factor erythroid 2-related factor signaling[101]. In addition, BRCA1/2 dysfunction may reduce cardiomyocyte resilience and enhance the carrier’s susceptibility to treatment-induced myocardial injury, which worsens long-term outcomes even when cancer control is achieved. Therefore, BRCA-related biology indirectly affects prognosis by shaping therapeutic efficacy and cardiovascular vulnerability[102]. In contrast, a recent study reported that BRCA1/2 mutations were not associated with CVD risk or enhanced cardiotoxicity. It is crucial to note that the authors stated the study power as one of their limitations[103]. Therefore, there is a need to explore the role of BRCA1/2 in cardio-oncology.

Ataxia telangiectasia mutated (ATM) serine/threonine kinase phosphorylates tumor protein p53 and BRCA1. Variation in ATM is associated with predisposition for ischemic heart disease and breast cancer. In pathway analysis, one of ATM associated pathway was DNA damage repair[27], which enhances the risk of cardiotoxicity in breast cancer patients and results in long-term poor prognosis.

Other genes with poor prognosis are tumor protein p53 and homologous recombination deficiency. In these tumors, tumor protein p53 and homologous recombination repair mutations are present, often associated with poor differentiation and a higher risk of recurrence[104], while the underlying DNA damage repair may enhance the cardiotoxicity of genotoxic chemotherapy[104,105]. In contrast, intact nuclear factor erythroid 2-related factor and antioxidant defenses are associated with cardiac tolerance to anthracyclines and trastuzumab, increasing the chance of more intensive treatment and improving long-term survival[104-106].

Finally, the time of CVD diagnosis is important in breast cancer, whereby if CVDs present during diagnosis of breast cancer, prognosis will be poor[107], and following cancer treatment, CVD prognosis depends on treatment type; for instance, left-sided radiation following mastectomy enhanced the risk of any CVDs in the Duch population. A later United States matched cohort found increased risks of deep vein thrombosis, pericarditis, HF, and valvular disease, with increased risks of arrhythmia, HF, pericarditis, and deep vein thrombosis that persisted > 5 years after cancer diagnosis[108]. In contrast different study reported that breast cancer patients in the Duch population have slightly lower CVD mortality risk compared with the general population[109].

CVD RISK PREDICTION IN BREAST CANCER VIA MACHINE LEARNING

The machine learning models for breast cancer survival prediction forecast patients likelihood of survival using patient data (genomic, mammographic, histopathological, protein, and clinical), helping doctors with personalized treatments and therapeutic outcomes. These machine learning models predict overall survival, disease-free survival, and various risk factors associated with breast cancer outcomes. Several machine learning models have been developed for breast cancer prognosis, predicting survival based on clinical variables, gene expression, and histopathological parameters, using publicly available breast cancer datasets as well as data from hospital records.

To predict the heart disease risks of breast cancer patients real-world electronic health records data, a long short-term memory model was developed, which predicts six CVDs: Congestive HF, coronary artery disease, cardiomyopathy, myocardial infarction, transient ischemic attack, and aortic regurgitation, with area under the receiver operating characteristics curve (AUC) scores ranging from 0.7189 to 0.9548, 12-24-month observation windows were found optimal for model performance. This study helped improve cardiovascular risk management in breast cancer patients[110]. The prospective cohort study was performed on 12413 breast cancer survivors without any prior CVD to evaluate the risk of occurrence of coronary artery disease. After a follow-up of 10.3 years, 750 incidents of fatal or non-fatal coronary artery events were recorded. A coronary artery disease-specific polygenic risk score can risk-stratify breast cancer survivors[111]. Stabellini et al[112] developed cancer-specific CVD risk scores using machine learning (XGBoost) for breast, colorectal, and lung cancer patients, incorporating cancer-related and socioeconomic predictors. The machine learning-derived scores significantly outperformed conventional CVD risk models (Pooled Cohort Equations, PREVENT, SCORE2), achieving high predictive accuracy for 10-year CVD risk, particularly in breast cancer patients. In a multicenter study of cancer survivors, regularized logistic regression and advanced machine learning models (random forests, Bayesian additive regression trees) showed comparable, strong performance in predicting multiple cardiovascular outcomes (AUCs of approximately 0.78-0.85). The findings highlight that robust, transferable machine learning-based risk models using longitudinal clinical data can effectively support cardiovascular risk stratification and prevention in cardio-oncology[113]. In 2023, Al-Droubi et al[114] developed and validated random forest and neural network models using electronic health record data to identify oncology patients at risk for CVD and support referrals to cardio-oncology, achieving > 90% accuracy and AUC, with the artificial neural network outperforming the random forest. The models provide a practical tool for integrating CVD risk assessment into oncology care, improving early detection and management of cardiotoxicity in cancer survivors. In another study, machine learning models (decision tree, random forest, XGBoost, AdaBoost) were applied to predict 180-day unplanned CVD readmissions in hospitalized cancer patients, with XGBoost performing best. Key predictors included length of stay, age, and cancer surgery, demonstrating that machine learning can effectively identify patients at high risk for CVD-related readmissions[115]. Chang et al[116] developed and validated artificial intelligence-based machine learning models, including multilayer perceptron, random forest, and support vector machine, to predict cancer therapy-related cardiac dysfunction and HF with reduced ejection fraction in breast cancer patients receiving anthracycline therapy. The multilayer perceptron model achieved the highest predictive performance (AUC up to 0.81), with key risk factors including trastuzumab use, hypertension, and anthracycline dose, demonstrating artificial intelligence’s potential to guide personalized cardio-oncology care. Various machine learning models offer a promising framework for predicting CVD risk in breast cancer patients using clinical, genomic, and publicly available datasets.

DISCUSSION

Over the last few decades, there has been huge progress in the survival of patients with breast cancer, in which it was doubled from 1970 to 2010; however, this improvement was associated with increased risk of CVDs, in which CVDs became the leading cause of death among breast cancer survivors[117,118].

The interplay between cardiovascular-associated genes and oncogenic regulators has been recognized as an important contributor to cancer outcomes. Emerging evidence indicates that molecular alterations involved in vascular integrity, immune signaling, and myocardial function can influence tumor behavior, while cancer-associated pathways may also aggravate cardiac and vascular injury. Shared mediators such as JAK2, TET2, and TTN[27], as well as signaling networks involving Wnt/β-catenin and GPCRs, participate in processes regulating inflammation, oxidative damage, angiogenesis, extracellular matrix turnover, and abnormal cell growth. Disruption of these interconnected mechanisms may foster a microenvironment conducive to disease progression, metastatic dissemination, and therapeutic resistance, ultimately affecting prognosis. In addition, treatment-associated cardiotoxic effects and mutation-driven clonal expansion may further strengthen this biological connection. These findings suggest that cardio-oncogenic interactions may serve as valuable indicators of recurrence risk and survival outcomes. Understanding this molecular convergence could advance biomarker identification, refine patient stratification, and support the development of integrated therapeutic strategies targeting both malignant progression and cardiovascular complications.

JAK2, particularly the V617F variant, has significant cardiovascular implications due to its association with myeloproliferative neoplasms, clonal hematopoiesis, thrombosis, and related cardiovascular complications[119]. In breast cancer, aberrant JAK2-signal transducer and activator of transcription 3 signaling has been associated with tumor progression and therapeutic resistance; however, JAK2 is not yet an established biomarker for treatment selection. TTN truncating variants are linked to dilated cardiomyopathy and may influence susceptibility to cancer therapy-related cardiac dysfunction, although their clinical utility for predicting cardiotoxicity remains to be confirmed[119,120]. Similarly, TET2 alterations, frequently observed in clonal hematopoiesis, may connect inflammation and cardiovascular risk with emerging cardio-oncology implications, but their routine clinical application remains unvalidated[121,122]. GRK4, AMPK, and PPAR-γ contribute to cardiovascular regulation, energy metabolism, and cancer-associated processes and are being explored as potential biomarkers[123,124]. Likewise, dysregulated Wnt/β-catenin signaling has been implicated in cardiovascular remodeling and breast cancer progression, metastasis, stemness, and treatment resistance[61,125]. Despite their biological and translational potential, these molecular alterations and pathways have not yet achieved sufficient clinical validation for routine use in diagnosis, risk stratification, prognosis, or therapeutic decision-making.

Machine learning-based approaches are increasingly transforming cancer-specific cardiovascular risk prediction by improving the ability to detect complex patterns that conventional statistical models may overlook. By integrating multidimensional clinical, genomic, imaging, and treatment-related data, these computational methods can support earlier identification of patients at elevated risk for cardiotoxicity and other adverse cardiovascular outcomes. Unlike traditional prediction tools, machine learning models can capture nonlinear relationships, dynamic interactions, and longitudinal trends, thereby enhancing risk stratification and prognostic assessment. In oncology settings, this is particularly relevant for evaluating cardiovascular complications associated with chemotherapy, targeted therapies, and radiation exposure. Emerging evidence suggests these models may aid personalized surveillance, optimize treatment planning, and inform preventive interventions. However, challenges related to data heterogeneity, model interpretability, external validation, and clinical implementation remain important considerations. Addressing these limitations will be essential to translating machine-learning-driven prediction tools into reliable strategies that improve cancer-specific cardiovascular risk management.

Pro-inflammatory cytokines such as TNF-α, IL-1β, IL-6, and TGF-β are key mediators that link oncogenic processes to cardiovascular pathology[67,68]. TNF-α, abundantly produced within the tumor microenvironment, not only supports cancer progression and metastasis but also promotes endothelial dysfunction by increasing vascular permeability, enhancing lipid deposition, and reducing nitric oxide bioavailability. These changes collectively accelerate atherogenesis and predispose individuals to ischemic events[74,76]. Similarly, IL-1β amplifies vascular inflammation by activating endothelial cells and upregulating adhesion molecules, facilitating leukocyte infiltration and perpetuating vascular injury. Its role in modulating downstream inflammatory pathways further reinforces its contribution to both tumor aggressiveness and atherosclerotic progression[81-83]. IL-6 serves as another important bridge between malignancy and cardiovascular complications, with its elevated levels correlating with poor breast cancer prognosis and enhanced inflammatory signaling in atherosclerosis. Its involvement in multiple cellular pathways highlights its dual impact on tumor biology and vascular disease progression[89,90]. Meanwhile, TGF-β adds a layer of complexity by promoting epithelial-to-mesenchymal transition and immune evasion in cancer[91], while simultaneously driving cardiac fibrosis and adverse myocardial remodeling following ischemic injury[94]. Integrated gene-cytokine-signaling networks linking breast cancer and CVD are summarized in Figure 2.

Figure 2 Integrated gene-cytokine-signaling networks linking breast cancer and cardiovascular disease. The figure illustrates the proposed biological relationships among Janus kinase 2, titin, Tet methylcytosine dioxygenase 2, G protein-coupled receptor kinase 4, AMP-activated protein kinase, peroxisome proliferator-activated receptor gamma, and wingless-related integration site/β-catenin, as well as their associated cytokine networks, intracellular signaling pathways, biological effects, and disease outcomes. Janus kinase 2 is linked to cytokine-mediated Janus kinase/signal transducer and activator of transcription signaling; titin to structural integrity and nuclear factor kappa B/transforming growth factor-β-small worm phenotype mothers against decapentaplegic-associated remodeling; Tet methylcytosine dioxygenase 2 to epigenetic regulation and inflammatory responses involving the NOD-, LRR- and pyrin domain-containing protein 3 inflammasome and nuclear factor kappa B; G protein-coupled receptor kinase 4 to G protein-coupled receptor-dependent mitogen-activated protein kinase/extracellular signal-regulated kinase and phosphoinositide 3-kinase/protein kinase B signaling; AMP-activated protein kinase to energy sensing and metabolic regulation; peroxisome proliferator-activated receptor gamma to lipid metabolism and anti-inflammatory signaling; and wingless-related integration site/β-catenin to cell proliferation, survival, angiogenesis, epithelial-mesenchymal transition, and fibrosis. JAK2: Janus kinase 2; TTN: Titin; TET2: Tet methylcytosine dioxygenase 2; GRK4: G protein-coupled receptor kinase 4; GPCR: G protein-coupled receptor; AMPK: AMP-activated protein kinase; PPAR-γ: Peroxisome proliferator-activated receptor gamma; Wnt: Wingless-related integration site; TNF-α: Tumor necrosis factor alpha; IL-6: Interleukin-6; IL-1β: Interleukin-1 beta; TGF-β: Transforming growth factor beta; JAK/STAT: JAK/signal transducer and activator of transcription; NF-κβ: Nuclear factor kappa B; SMAD: Small worm phenotype mothers against decapentaplegic; NLRP3: NOD-, LRR- and pyrin domain-containing protein 3; MAPK: Mitogen-activated protein kinase; ERK: Extracellular signal-regulated kinase; PI3K/AKT: Phosphoinositide 3-kinase/protein kinase B; EMT: Epithelial-mesenchymal transition.

Collectively, these findings underscore a shared inflammatory axis that integrates breast cancer progression with cardiovascular dysfunction. Understanding this crosstalk not only provides mechanistic insight into the increased cardiovascular risk observed in breast cancer patients but also highlights potential therapeutic targets. Therapeutic approaches targeting inflammatory signaling pathways may offer dual benefits by mitigating tumor progression and reducing cardiovascular complications, thereby improving overall survival. The gene interaction and molecular pathways linking breast cancer and CVDs are summarized in Figure 3.

Figure 3 Schematic representation of integrated analysis of shared genes and molecular pathways in cardiovascular disease progression and breast cancer outcomes. The figure summarizes the molecular pathways and key regulatory genes that contribute to the bidirectional relationship between cardiovascular disease (CVD) and cancer. Central shared genes, including Janus kinase 2, titin, and Tet methylcytosine dioxygenase 2, are associated with both cardiovascular and oncogenic processes and serve as critical nodes linking disease pathogenesis. These genes influence three major biological pathways: (1) Inflammatory signaling, involving cytokines (interleukin-1, tumor necrosis factor-α, interferon-γ), nuclear factor kappa B, hypoxia-inducible factor-1α, and signal transducer and activator of transcription activation; (2) Metabolic regulation, encompassing AMP-activated protein kinase-mediated energy homeostasis, lipid and glucose metabolism, and oxidative stress responses; and (3) Cellular proliferation and survival, including cell-cycle progression, DNA damage responses, epithelial-mesenchymal transition, and angiogenesis. These pathways converge to promote chronic inflammation and oxidative stress, representing common mechanistic links between CVD and cancer. Key molecular regulators linking CVD and cancer include bromodomain-containing protein 4, dual-specificity tyrosine-phosphorylation-regulated kinase 1B, wingless-related integration site/β-catenin-SRY-Box transcription factor 17 signaling, G protein-coupled receptor kinase 4, AMP-activated protein kinase, peroxisome proliferator-activated receptor-γ, and plasminogen activator inhibitor-1, which collectively regulate cellular proliferation, metabolism, fibrosis, angiogenesis, vascular remodeling, and therapeutic resistance. The convergence of these pathways results in common pathological outcomes, including chronic inflammation, oxidative stress, uncontrolled cellular proliferation, angiogenesis, tissue fibrosis and remodeling, therapy resistance, and disease progression. JAK2: Janus kinase 2; TTN: Titin; TET2: Tet methylcytosine dioxygenase 2; CVD: Cardiovascular disease; CHIP: Clonal hematopoiesis of indeterminate potential; CAD: Coronary artery disease; IL-1: Interleukin-1; TNF-α: Tumor necrosis factor-alpha; IFN-γ: Interferon-gamma; NF-κB: Nuclear factor kappa B; HIF-1α: Hypoxia-inducible factor-1 alpha; STAT: Signal transducer and activator of transcription; AMPK: AMP-activated protein kinase; ROS: Reactive oxygen species; EMT: Epithelial-mesenchymal transition; CRP: C-reactive protein; DNMT3A: DNA methyltransferase 3A; BRD4: Bromodomain-containing protein 4; DYRK1B: Dual-specificity tyrosine-phosphorylation-regulated kinase 1B; Wnt: Wingless-related integration site; SOX17: SRY-Box transcription factor 17; PAH: Pulmonary arterial hypertension; GRK4: G protein-coupled receptor kinase 4; GPCR: G protein-coupled receptor; BP: Blood pressure; PI3K: Phosphoinositide 3-kinase; mTOR: Mechanistic target of rapamycin; p53: Tumor protein p53; PPAR-γ: Peroxisome proliferator-activated receptor gamma; VSMC: Vascular smooth muscle cell; PAI-1: Plasminogen activator inhibitor-1.

In addition, using artificial intelligence and machine learning, omics data, such as transcriptomic data, can be analyzed alongside survival and other patient outcome data to provide further mechanistic insights into how genetic and traditional markers may converge to influence disease behavior. This can shed light on why some cancer subtypes are associated with more cardiotoxicity than others.

FUTURE DIRECTIONS

There are many molecular and signaling pathways, such as inflammation, oxidative stress, angiogenesis, nuclear factor kappa B signaling, and TGF-β signaling, that are common in breast cancer and CVDs. But the interplay between these pathways and signaling processes, aimed at identifying common molecular targets that influence both diseases, has never been studied. The multi-omics data have been studied in breast cancer and CVDs separately. Still, the crosstalk between CVD-associated gene networks and breast cancer signaling pathways has not yet been studied. Cardiovascular-oncogenic gene networks based on multi-omics datasets and the identification of hub and regulatory networks shared between the two diseases have not yet been explored. Cardio-oncology research needs to focus on multi-omics approaches rather than single-gene investigations to link CVD and breast cancer. Thus, integrating genomics, transcriptomics, proteomics, metabolomics, etc., can provide a better understanding of how CVD-associated genes are differentially expressed in breast cancer and their clinical relevance for breast cancer survival prediction and therapeutic strategies. There are limited studies on linking CVDs and breast cancer at the molecular level, predictive gene signatures identifications based on the omics databases.

CONCLUSION

Many machine learning models for breast cancer survival and prognosis have been developed based on clinical, genetic features, and tumor biology. Still, the cardio-specific biomarkers and CVD genes, which are differentially expressed in breast cancer patients, have never been used for the development of any such model. Pre-existing cardiovascular risk or identification of CVD-associated genes in breast cancer patients can affect long-term survival; the development of a breast cancer survival model based on cardio-specific biomarkers can help clinicians provide better patient care and precision treatment. Although cardiovascular complications and/or CVD genes and involved molecular pathways can significantly impact cancer survival and therapeutic response, different machine learning models (traditional, ensemble, or deep learning) are required to integrate cardio-specific biomarkers into cancer survival prediction frameworks. Differentially expressed CVD genes in breast cancer patients genome-wide association study, RNA-seq datasets, and omics databases have never been integrated into breast cancer survival models into breast cancer survival models. There are a few machine learning models that deal with the risk of CVD in cancer patients due to therapy, but not focused on breast cancer survival prediction based on differentially expressed CVD genes and cardiovascular gene-driven risk stratification. Also, a few studies in cardio-oncology are based on hospital records and small datasets, but none have been conducted on multi-omics datasets. 5-year or 10-year breast cancer survival and how CVD genes affect the long-term outcomes in breast cancer patients have not been studied. The breast cancer survival models developed based on differentially expressed genes associated with other pathological conditions need to be validated by different publicly available datasets, as well as real-time data from the patients.

ACKNOWLEDGEMENTS

We acknowledge Mahatma Gandhi Central University, Motihari, India, and Guru Ghasidas Vishwavidyalaya, Bilaspur, Chhattisgarh, India, for providing the necessary infrastructure to carry out the work. We want to acknowledge Dr. Tapan Sharma, UMASS, United States, for providing the necessary help for editing and corrections of the manuscript. Shikha Bhardwaj is a recipient of a CSIR fellowship.