Gastric cancer remains one of the deadliest cancers globally due to delayed detection and limited treatment options, underscoring the critical need for innovative prognostic methods. Disulfidptosis, a recently discovered programmed cell death triggered by disulphide stress, presents a fresh avenue for therapeutic exploration. This research examines disulfidptosis-related long noncoding RNAs (DRLs) in gastric cancer, with the goal of leveraging these lncRNAs as potential markers to enhance patient outcomes and treatment approaches. Comprehensive genomic and clinical data from stomach adenocarcinoma (STAD) were obtained from The Cancer Genome Atlas (TCGA). Employing least absolute shrinkage and selection operator (LASSO) regression analysis, a prognostic model was devised incorporating five key DRLs to forecast survival rates. The effectiveness of this model was validated using Kaplan-Meier survival plots, receiver operating characteristic (ROC) curves, and extensive functional enrichment studies. The importance of select lncRNAs and the expression variability of genes tied to disulfidptosis were validated via quantitative real-time PCR (qRT-PCR) and Western blot tests, establishing a solid foundation for their prognostic utility. Analyses of functional enrichment and tumour mutation burden highlighted the biological importance of these DRLs, connecting them to critical cancer pathways and immune responses. These discoveries broaden our comprehension of the molecular framework of gastric cancer and bolster the development of tailored treatment plans, highlighting the substantial role of DRLs in clinical prognosis and therapeutic intervention.

Immunotherapy is firmly established as a treatment regimen in various solid tumors, driven by its exceptional benefits in a selected group of patients. Despite widespread adoption of immune checkpoint blockade (ICB) across diverse solid tumors, the quest for a clinically informative biomarker for long-term benefit remains unmet.

A total of 49 patients with metastatic NSCLC treated with ICB were included. Long-term (LTR) and short-term responders (STR) were defined as those with a response to ICB lasting more than 24 months or less than 6 months, respectively. Longitudinal blood specimens were collected before ICB treatment initiation and early-on treatment. Plasma ctDNA next-generation sequencing panel (NGS) and serum proteomics were performed. GeoMx DSP on baseline tumor tissue was performed in a subset of patients.

Our analysis revealed specific characteristics of LTR compared with STR, namely higher PD-L1 in tumor cells (p = 0.005) and higher incidence of irAEs (p = 0.001). Genomic features associated with lack of benefit from ICB included co-occurring mutations in KRAS/STK11 and TP53/KMT2D (p < 0.05). At a baseline, LTR patients exhibited higher serum levels of proteins related with apoptosis (CASP8, PRKRA), chemotaxis, immune proteasome, processing of MHC class I (S100A4, PSMD9, RNF41) and immune homeostasis (HAVCR1, ARG1) (p < 0.05). Protein spatial profiling of tumor samples showed higher levels of proteins linked with the presence of immune cells (CD45), T cells (CD8), antigen presentation (HLA-DR) and immune regulation proteins (PD-L1, IDO1) within the tumor and tumor stroma component (p < 0.05) in LTR patients. Serum longitudinal analysis identified a set of proteins that presented distinct dynamics in LTR compared to STR, making them interesting candidates to evaluate as early predictors of treatment efficacy.

Our multimodal analysis of patients with metastatic NSCLC treated with ICB identified clinicopathological and immunological features associated with long-term benefits. The presence of preexisting antitumor immunity emerged as a strong predictor of long-term benefits, providing insights for potential biomarkers and therapeutic strategies for enhancing ICB outcomes in metastatic NSCLC.

Pancreatic neuroendocrine neoplasms (pNENs) are rare and heterogeneous tumors arising from neuroendocrine cells, representing approximately 10 % of all Gastro-Entero-Pancreatic neuroendocrine neoplasms. While most pNENs are sporadic, a subset is associated with genetic syndromes such as multiple endocrine neoplasia type 1 (MEN1) or von Hippel-Lindau disease (VHL). pNENs are further classified into functioning and non-functioning tumors, with distinct clinical behaviors, prognoses, and treatment approaches. This review explores genetic and environmental biomarkers that influence the risk, prognosis, and therapeutic responses in pNENs. The epidemiology of pNENs reveals an increasing incidence, primarily due to advancements in imaging techniques. Genetic factors play a pivotal role, with germline mutations in MEN1, VHL, and other genes contributing to familial pNENs. Somatic mutations, including alterations in the mTOR pathway and DNA maintenance genes such as DAXX and ATRX, are critical in sporadic pNENs. These mutations, along with epigenetic dysregulation and transcriptomic alterations, underpin the diverse clinical and molecular phenotypes of pNENs. Emerging evidence suggests that epigenetic changes, including DNA methylation profiles, can stratify pNEN subtypes and predict disease progression. Environmental and lifestyle factors, such as diabetes, smoking, and chronic pancreatitis, have been linked to an increased risk of sporadic pNENs. While the association between these factors and tumor progression is still under investigation, their potential role in influencing therapeutic outcomes warrants further study. Advances in systemic therapies, including somatostatin analogs, mTOR inhibitors, and tyrosine kinase inhibitors, have improved disease management. Biomarkers such as Ki-67, somatostatin receptor expression, and O6-methylguanine-DNA methyltransferase (MGMT) status are being evaluated for their predictive value. Novel approaches, including the use of circulating biomarkers (NETest, circulating tumor cells, and ctDNA) and polygenic risk scores, offer promising avenues for non-invasive diagnosis and monitoring. Despite these advancements, challenges remain, including the need for large, well-annotated datasets and validated biomarkers. Future research should integrate multi-omics approaches and leverage liquid biopsy technologies to refine diagnostic, prognostic, and therapeutic strategies. Interdisciplinary collaborations and global consortia are crucial for overcoming current limitations and translating research findings into clinical practice. These insights hold promise for improving prevention, early detection, and tailored treatments, ultimately enhancing patient outcomes.

The field of rare cancer research is rapidly transforming, marked by significant progress in clinical trials and treatment strategies. Rare cancers, as defined by the National Cancer Institute, occur in fewer than 150 cases per million people each year, yet they collectively represent a significant portion of all cancer diagnoses. Because of their infrequency, these cancers pose distinct challenges for clinical trials, including limited patient populations, geographical dispersion, and a general lack of awareness of treatment options. Economic limitations further complicate drug development, making initiatives such as the Orphan Drug Act essential for incentivizing research. The advent of next-generation sequencing (NGS) and precision medicine has been instrumental in identifying actionable genetic alterations in parallel with an explosion in the development of genomically targeted therapies, immunotherapies, and antibody drug conjugates. Advances in clinical NGS, precision medicine, and tumor-agnostic therapies have become central to the progress in rare cancer research. The development and approval of tumor-agnostic drugs, such as BRAF, NTRK, and RET inhibitors, and immunotherapy for mismatch repair deficient/microsatellite instability-high status cancers highlight the potential of personalized treatments across diverse cancer types and across the age spectrum. Collaborative trials from cooperative groups including SWOG DART, ASCO TAPUR, NCI-MATCH, pediatric COG-match, DRUP, IMPRESS, and innovative registrational basket and platform trials (eg, VE-Basket, ROAR, LIBRETTO-001, ARROW), along with patient advocacy group-run trials like TRACK, are enhancing access to clinical trials. In addition, artificial intelligence has the potential to improve the trial matching process. An integrated approach, combining these innovations in collaboration with multiple stakeholders, is crucial for advancing rare cancer research, offering hope for better patient outcomes and quality of life.

Despite the increased incidence of thyroid cancer due to enhanced precision of ultrasound technology and extensive utilization of puncture aspiration cytology, the mortality rate remains low, raising concerns about overdiagnosis. Papillary thyroid carcinoma (PTC) is the most common type, primarily diagnosed through cell nuclei examination. Recent advancements in identifying genetic mutations and tumor classification have refined diagnostic methods. Point mutations in the telomerase reverse transcriptase promoter (TERTp), specifically -124 C >T (C228T) and -146 C >T (C250T), and the regulatory single nucleotide polymorphism -245 T >C, C allele of rs2853669 (TrSNP) are potential thyroid cancer biomarkers. The present study tested the hypothesis that the coexistence of BRAF mutations in driver genes upstream of the MAPK pathway and late mutations unrelated to signaling, such as point mutations in TERTp, increases tumor virulence. A total of 133 patients with PTC who underwent surgery between January 2014 and November 2021 were included in the study. Blood and tumor tissue samples were collected, and DNA was extracted for genetic mutation analysis using PCR and Sanger sequencing. The TrSNP analysis of blood and surgical tissue samples showed a 97.7% agreement rate. TrSNP was detected in 70 of 133 patients (52.6%) and was significantly associated with tumor size, particularly in tumors >2.0 cm. TERTp point mutations were identified in 29 of 133 patients (21.8%), with C228T strongly associated with tumor size, particularly in tumors >4.0 cm, and extraglandular invasion. BRAF V600E was detected in 82 patients (61.7%) but showed no significant association with clinicopathological parameters. However, the coexistence of BRAF V600E with C228T and TrSNP affected tumor size and progression. The findings indicated that TrSNPs, along with C228T and BRAF V600E, may serve as potential molecular markers to predict PTC growth or exacerbation. Notably, coexistence of C228T and TrSNP is a preoperative indicator of disease progression.

Immune checkpoint blockage (ICB) therapy has shown minimal effectiveness in anaplastic lymphoma kinase (ALK)-positive nonsmall cell lung cancer (NSCLC) regardless of Programmed death-ligand 1 expression. ALK fusion accompanied by mismatch repair deficiency or microsatellite instability-high (MMRd/MSI-H) and high tumor mutation burden (TMB-H) are extremely rare in NSCLC, and the efficacy of ALK inhibitors or ICB-based therapies is unclear. Here, we report the case of a 60-year-old female patient with metastatic lung adenocarcinoma accompanied by EML4-ALK fusion, TMB-H, MMRd/MSI-H, and pathogenic mutations in TP53, MLH1, and STK11. The patient experienced progression on initial iruplinalkib and subsequent alectinib therapy within 5 months. After the failure of third-line therapy with cisplatin-pemetrexed combined with bevacizumab, she received sintilimab plus anlotinib which led to a progression-free survival of 6.5 months. She received sintilimab combined with albumin-paclitaxel plus carboplatin and achieved partial response after 6 months. She developed adverse events after one cycle of sintilimab plus albumin-paclitaxel treatment. Then she was continued with sintilimab plus anlotinib as a maintenance therapy due to intolerance to chemotherapy. After progression on ICB-based therapy, the patient was treated with lorlatinib and still under follow-up with overall survival of more than 3 years. Our findings highlight the therapeutic potential of ICB-based regimens in patients with MSI-H and ALK-rearranged NSCLC.

Responses to immune checkpoint inhibitors (ICIs) differ significantly between uveal melanoma (UM) and cutaneous melanoma (CM) patients. We investigated the immune profile of metastatic UM(mUM) patients and identified markers that are predictive of improved survival. Metastatic liver samples from 189 UM patients and 48 CM patients were analyzed at genomic and transcriptional levels, and survival analysis was performed on a subgroup of 76 ICI-treated mUM patients. UM liver metastases seem to preserve the genomic and immune characteristics of primary UM (pUM), with a low prevalence of ICI markers and high mutation rates of GNA11, GNAQ, BAP1, and SF3B. Compared with mCM, UM liver metastasis showed lower infiltration of several immune cells, but a greater proportion of M2 macrophages. Compared with UM liver metastases, CM liver metastases showed higher expression of G2M checkpoint and EF2 target genes. Among the mUM and mCM samples, expression of G2M and E2F pathway genes was highest in tumors with high TMB values and T-cell inflamed scores. A longer median overall survival (OS) was observed in mUM patients with higher expression of LAG3, HLA class I, or HLA class II; which may represent a small proportion of immune hot tumors. Expression patterns of G2M checkpoint and E2F targets suggest a possible contribution to immunotherapy response.

Pancreatic adenocarcinoma remains one of the most aggressive and difficult-to-treat solid tumor malignancies, with a high mortality-to-incidence ratio. Globally, pancreatic cancer ranks 12th in terms of incidence but sixth for mortality signifying its aggressive behavior and limited treatment options. While the mortality rates for many other solid tumors have substantially improved over the past few decades, temporal trends in pancreatic cancer mortality rates are quite sobering. In the United States, from 2000 to 2020, the mortality rates from pancreatic cancer have increased, whereas at the same time, mortality rates from other cancers, such as lung, colorectal, or kidney, have fallen appreciably. Is this for lack of treatment innovation? How do we improve survival for patients with pancreatic cancer? In this chapter, we discuss the recent advances and future directions with targeted therapies and immunotherapies in the treatment of pancreatic cancer, and provide the reasons for both optimism and caution for the future of systemic treatment of pancreatic cancer.

Immune checkpoints are crucial in regulating the activation of cell-mediated and humoral immune responses. However, cancer cells hijack this mechanism to evade the immune surveillance and anti-cancer response. Typically, receptors like PD-1 and CTLA4, expressed on immune cells, prevent the activation and differentiation of T cells. They also inhibit the development of autoimmune reactions. However, ligands such as PD-L1 for the receptor PD-1 are also expressed on the surface of cancer cells that help prevent the activation of anti-cancer immune responses by blocking the signalling pathways mediated by PD-1 and CTLA4. Immune checkpoint inhibitors (ICIs) have promising therapeutic efficacy for treating several cancers by activating T cells and their differentiation into effector cells against tumours. Nonetheless, hyperactivated immune cells usually contribute to detrimental issues, also known as immune-related adverse effects (IrAE). IrAEs have been observed in multiple organs, leading to neurological issues, colitis, endocrine dysfunction, renal issues, hepatitis, pneumonitis, and dermatitis. The interplay between hyperactivated T cells and Treg cells helps in orchestrating the development of autoimmunity. Moreover, the crosstalk between proinflammatory interleukins and the development of autoantibodies also mediates the multiorgan effects of ICIs in cancer patients. IrAEs are generally managed by terminating the ICI therapy, reducing the ICI dose, and by using corticosteroids to subvert inflammation. Therefore, the present review aims to delineate the impacts of ICIs on the development of autoimmune diseases and inflammatory outcomes in cancer patients. In addition, mechanistic insight involving immune cells, cytokines, and autoantibodies for ICI-mediated IrAEs will also be discussed with updated findings in this field.

Immune checkpoint inhibitors (ICIs) are potent and precise therapies for various cancer types, significantly improving survival rates in patients who respond positively to them. However, only a minority of patients benefit from ICI treatments.

Identifying ICI responders before treatment could greatly conserve medical resources, minimize potential drug side effects, and expedite the search for alternative therapies. Our goal is to introduce a novel deep-learning method to predict ICI treatment responses in cancer patients.

The proposed deep-learning framework leverages graph neural network and biological pathway knowledge. We trained and tested our method using ICI-treated patients' data from several clinical trials covering melanoma, gastric cancer, and bladder cancer.

Our results demonstrate that this predictive model outperforms current state-of-the-art methods and tumor microenvironment-based predictors. Additionally, the model quantifies the importance of pathways, pathway interactions, and genes in its predictions. A web server for IRnet has been developed and deployed, providing broad accessibility to users at https://irnet.missouri.edu.

IRnet is a competitive tool for predicting patient responses to immunotherapy, specifically ICIs. Its interpretability also offers valuable insights into the mechanisms underlying ICI treatments.

Macromolecular Drugs (including monoclonal antibodies, recombinant proteins, and nucleic acid therapies) have become a cornerstone strategy for intervening in complex pathological mechanisms such as cancer, autoimmune diseases, and genetic disorders due to their high specificity for disease targets and low off-target toxicity. However, compared to traditional small-molecule drugs, the high molecular weight (>10 kDa) and structural complexity of macromolecular drugs result in extremely low transmembrane permeability. This is particularly challenging in the treatment of central nervous system (CNS) diseases, where the blood-brain barrier (BBB) imposes stringent selectivity, further limiting drug delivery efficiency. This review focuses on the breakthrough strategy of nose-to-brain (NtB) drug delivery. On one hand, the NtB pathway bypasses the BBB, enabling direct CNS drug delivery. On the other hand, nanocarrier technology can synergistically achieve systemic delivery and brain-targeted transport. Based on the latest research advances, this article systematically examines the feasibility of delivering macromolecular drugs via NtB administration. We comprehensively summarize relevant delivery carriers and discuss the potential advantages of intranasal-brain delivery for CNS disease treatment. Notably, while significant progress has been made in this field, further exploration is still needed regarding the mechanisms of NtB delivery and challenges in clinical translation.

Immune checkpoint inhibitors (ICIs) have shown substantial benefit for patients with advanced non-small cell lung cancer (NSCLC). However, resistance to ICIs remains a major clinical challenge. Here, we perform a comprehensive bioinformatic analysis of plasma proteomic profiles to explore the underlying biology of treatment resistance in NSCLC.

The analysis was performed on 388 "resistance-associated proteins" (RAPs) that were previously described as pretreatment plasma proteomic predictors within the PROphet computational model designed to predict ICI clinical benefit in NSCLC. Putative tissue origins of the RAPs were explored using publicly available datasets. Enrichment analyses were performed to investigate RAP-related biological processes. Plasma proteomic data from 50 healthy subjects and 272 patients with NSCLC were compared, where patients were classified as displaying clinical benefit (CB; n=76) or no CB (NCB; n=196). Therapeutic agents targeting RAPs were identified in drug and clinical trial databases.

The RAP set was significantly enriched with proteins associated with lung cancer, liver tissue, cell proliferation, extracellular matrix, invasion, and metastasis. Comparison of RAP expression in healthy subjects and patients with NSCLC revealed five distinct RAP subsets that provide mechanistic insights. The RAP subset displaying a pattern of high expression in the healthy population relative to the NSCLC population included multiple proteins associated with antitumor activities, while the subset displaying a pattern of highest expression in the NCB population included proteins associated with various hallmarks of treatment resistance. Analysis of patient-specific RAP profiles revealed inter-patient diversity of potential resistance mechanisms, suggesting that RAPs may aid in developing personalized therapeutic strategies. Furthermore, examination of drug and clinical trial databases revealed that 17.5% of the RAPs are drug targets, highlighting the RAP set as a valuable resource for drug development.

The study provides insight into the underlying biology of ICI resistance in NSCLC and highlights the potential clinical value of RAP profiles for developing personalized therapies.

This multicenter phase Ib/II trial aimed to evaluate the safety and efficacy of combining durvalumab, tremelimumab, and paclitaxel as second-line treatment for biomarker-selected patients with metastatic gastric cancer.

In phase Ib, the standard 3 + 3 dose escalation method was used. Durvalumab and tremelimumab were administered every 4 weeks for 13 and 4 cycles, respectively, combining paclitaxel 80 mg/m2 (dose level 2) or 60 mg/m2 (dose level 1) on days 1, 8, and 15. The primary outcome for phase II was the objective response rate (ORR).

In phase Ib (n = 7), dose level-1 was selected as the recommended phase II dose. In phase II, 48 patients were enrolled: microsatellite instability-high or deficient mismatch repair protein tumors (n = 16); EBV-positive tumors (n = 15); high tumor mutation burden ( ≥ 5/Mb) (n = 11); CD274 amplification (n = 5); and POLD1 mutation (n = 1). The ORR was 52.1%, meeting the primary endpoint. The median progression-free survival and overall survival were 5.3 and 13.1 months, respectively. The most common any-grade and grade 3-4 adverse events were anemia (41.7%) and neutropenia (10.4%), respectively.

Durvalumab-tremelimumab with paclitaxel was tolerable and efficacious in biomarker-selected gastric cancer patients as a second-line treatment, highlighting the importance of biomarker-based approaches for immunotherapy in gastric cancer.

NCT03751761.

Addressing existing racial disparity in breast cancer is crucial to ensure equitable benefit across diverse communities. We evaluate the molecular and clinical effects of genetic ancestry in African and South Asian women compared to European using a combined cohort of 7136 breast cancer patients. We find that non-European patients present significantly earlier and die at a younger age. The African group has an increased prevalence of higher grade and hormone receptor negative disease. The South Asian group shows tendency towards lower stage at diagnosis and tumour mutational burden. We observe differences and similarities in the somatic mutational landscape, and differences in germline mutation rates relevant to genetic testing and breast cancer predisposition. Potential therapeutic candidates are identified, with a higher propensity for homologous recombination deficiency serving as a therapy response indicator. We harness breast cancer multimodal data to improve understanding of ancestry-associated differences and highlight opportunities to advance health equity.

Tumor Mutation Burden (TMB) is commonly characterized as the number of non-synonymous somatic SNVs per megabase within the gene region identified through whole exon sequencing or targeted sequencing in a tumor sample. It has been statistically demonstrated that TMB was related to the ability of neoantigen production and used to predict the efficacy of immunotherapy for various types of cancers. However, screening for TMB in patients poses challenges due to the extensive labor and financial resources required for the preparation of large quantities of parallel sequencing libraries.

In this study, we employed compressed sensing (CS) to calculate TMB from overlapped pooling sequencing data, aiming to reduce the sequencing cost by minimizing the number of library builds. Over 90% SNPs could still be detected without a significant loss of mutation information even when the data is pooled from ten different samples. Based on this, the orthogonal matching pursuit (OMP) algorithm and the basic pursuit (BP) algorithm were used to reconstruct TMB from pooling sequencing data. The performance of these two algorithms was evaluated. The BP algorithm consistently performed well across all cases, albeit necessitating extended computational time. The OMP algorithm has been proved to be suitable for scenarios where the original matrix was sparse but it showed low overall performance. Based on an accurate calculation of TMB, we determined that the number of sequencing runs could be reduced to 0.6 times the total number of samples, resulting in a 40% reduction in sequencing cost.

In conclusion, we calculated TMB from overlapped pooling sequencing data utilizing compressed sensing strategy to reduce sequencing cost. Our findings confirm that the SNP calling from ten samples' pooling sequencing data is feasible. Additionally, we performed an assessment of the reconstruction efficiency of both the BP model and the OMP model.

The rapid development of immunotherapy has shown preliminary clinical efficacy and significant anti-tumor effects in some cancer patients. Although immunotherapy has been approved for breast cancer, some breast cancer patients still do not benefit from it due to issues such as immunotherapy insensitivity and resistance. Mass cytometry, as a mature single-cell proteomic analysis method, with its high-throughput capabilities, has been widely used in the analysis of tumor immune microenvironments and immune cell subpopulations. Using mass cytometry to analyze the immune microenvironment of breast cancer and explore new immunotherapy targets can help improve the current status of breast cancer immunotherapy and develop personalized treatment plans for more patients. This review surveys the recent advancements in analyzing the single-cell components of breast cancer using mass cytometry technology and reviews the immune microenvironment of breast cancer as well as potential targets for immunotherapy. These results provide new insights for the subsequent research of the immune microenvironment of breast cancer and targeted immunotherapy.

Cutaneous angiosarcoma (cAS) is a rare and aggressive malignant vascular tumor that arises from endothelial cells lining the blood vessels. It can occur in any part of the body, but most commonly, it affects the skin and soft tissues. cAS has a poor prognosis with a 5-year survival rate of only 9%. This review summarizes the current understanding of angiosarcoma pathogenesis, clinical presentation, diagnosis, and treatment approaches. Recent advances in molecular characterization have identified recurrent genetic alterations that may lead to the development of novel targeted therapies. Multidisciplinary management combining surgery, radiation, and systemic therapy remains the mainstay of treatment; however, outcomes remain poor for metastatic disease. Ongoing research into the molecular drivers of cAS and immunotherapeutic approaches offers hope for improving the outcomes of this challenging malignancy.

In the phase II NIMBUS trial, patients with human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer (MBC) and high tumor mutational burden (TMB ≥ 9 mut/Mb) received nivolumab (3 mg/kg biweekly) and low-dose ipilimumab (1 mg/kg every 6 weeks) for 2 years or until progression. The primary endpoint was objective response rate (ORR) per RECIST 1.1 criteria. Among 30 patients enrolled, the median TMB was 10.9 mut/Mb (range: 9-110) and the confirmed objective response rate was 20%. Secondary endpoints included progression-free survival, overall survival, clinical benefit rate, and safety and tolerability, including immune-related adverse events (irAEs). A prespecified correlative outcome was to evaluate the ORR in patients with a TMB ≥ 14 mut/Mb. Patients with TMB ≥ 14 mut/Mb (n = 6) experienced higher response rates (60% vs 12%; p = 0.041) and showed a trend towards improved progression-free survival and overall survival compared to patients with TMB < 14 mut/Mb. Exploratory genomic analyses suggested that ESR1 and PTEN mutations may be associated with poor response, while clinical benefit was associated with a decrease or no change in tumor fraction by serial circulating tumor DNA during treatment. Stool microbiome analysis revealed that baseline blood TMB, PD-L1 positivity, and immune-related diarrhea are associated with distinct taxonomic profiles. In summary, some patients with hypermutated HER2-negative MBC experience extended clinical benefit with a dual immunotherapy regimen; a higher TMB, and additional genomic and microbiome biomarkers may optimize patient selection for therapy with nivolumab plus low-dose ipilimumab. (Funded by Bristol Myers Squibb; ClinicalTrials.gov identifier, NCT03789110).

The GAINED study was a randomized phase 3 trial comparing obinutuzumab (G) with rituximab (R) plus ACVBP (doxorubicin, cyclophosphamide, and prednisone, combined with either vindesine or bleomycin) or CHOP14 (cyclophosphamide, doxorubicin, vincristine, and prednisone, administered on a 14-day schedule) induction, followed by positron emission tomography (PET)-guided consolidation. This post hoc analysis aimed to detail the outcomes of patients with primary mediastinal B-cell lymphoma (PMBL), verified through expert pathological review and the use of gene expression profiling (GEP) and next-generation sequencing. Of 620 centrally reviewed patients, 138 (22.3%) confirmed PMBL cases were analyzed. Baseline characteristics included a median age of 33.5 years, 63.8% female, 55.1% stage III to IV, 90.6% elevated lactate dehydrogenase, 87.6% Eastern Cooperative Oncology Group performance status score of 0 to 1, 62.3% extranodal involvement, 52.6% age-adjusted International Prognostic Index (aaIPI) of 2% to 3%, and 53.6% bulk (>10 cm). Induction regimens were R/G-CHOP14 (56.9%) and R/G-ACVBP (43.1%). Postinduction treatments, based on interim PET results, included: standard consolidation chemotherapy (59.8%) if change in maximum standardized uptake value (ΔSUVmax) of >66% after cycle 2 and >70% after cycle 4 (PET2-/4-), intensive treatment and autologous transplantation (26.8%) if PET2+/4-, and salvage therapy (13.4%) if PET4+ (ΔSUVmax of ≤70%). Among patients with GEP data (n = 107), 38 (35.5%) were PDL1high/PDL2high. Key somatic mutations data (n = 87) included SOCS1 (70.1%), B2M (56.3%), STAT6 (49.4%), TNFAIP3 (47.1%), GNA13 (39.1%), CIITA (37.9%), CD58 (36.8%), and TP53 (29.9%). After a median follow-up of 39.5 months, 2-year progression-free survival (PFS) and overall survival (OS) rates were 86.2% and 93.2%, respectively. In a multivariate model including bulk, aaIPI, and ΔSUVmax PET2/PET4, only bulk and ΔSUVmax PET4 of ≤70% were associated with shorter PFS (hazard ratio, 4.39 [95% confidence interval (CI), 1.28-15.11] and 4.95 [95% CI, 1.71-14.3], respectively), whereas none were associated with OS. The ΔSUVmax-based interim PET4 response emerged as the strongest predictor of patient outcomes in this selected clinical trial population. This trial was registered at www.ClinicalTrials.gov as #NCT01659099.

The nuclear receptor TR4 binding protein, TRA16, has been implicated in lung carcinogenesis; however, its broader role across diverse human cancers remains poorly understood. Understanding TRA16's involvement in cancer biology could uncover novel regulatory mechanisms and potential therapeutic targets.

We conducted a comprehensive pan-cancer analysis of TRA16 expression and function across multiple human malignancies. Gene co-expression networks, pathway enrichment, transcription factor analysis, organoid modeling, and intercellular communication profiling were employed. Tumor mutation burden (TMB) and microenvironmental features were also assessed in relation to TRA16 expression, stratified by TP53 mutation status.

Correlation analysis identified the cell cycle as the top enriched pathway among TRA16-associated genes, with key transcription factors, including RB-E2F, MYC, and TP53, regulating genes co-expressed with TRA16. In liver cancer organoid models, TRA16 and its co-expressed genes were significantly upregulated. Intercellular communication analysis showed that TRA16-positive cells exhibited increased autocrine signaling and overall signaling activity. Importantly, patients with high TRA16 expression demonstrated elevated TMB and decreased stromal and immune features.

These findings highlight TRA16 as a potential master regulator of oncogenic processes, contributing to tumor progression through coordinated regulation of cell cycle genes, intercellular signaling, and genomic instability. Our results provide new insights into TRA16's role across cancers and support its potential as a novel oncogene.

Endometrial carcinoma (EC) is the sixth most prevalent malignancy among women globally, posing a significant clinical challenge due to limited therapeutic options for advanced or recurrent cases. The identification of novel prognostic biomarkers and therapeutic targets is crucial for improving patient outcomes. This study aimed to investigate the multifaceted roles of MYB Proto-Oncogene Like 2 (MYBL2) in uterine corpus endometrial carcinoma (UCEC).

We employed multiple bioinformatics algorithms (GEPIA, TCGA, TIMER2.0) to analyze MYBL2 expression across different cancer types and in UCEC specifically. Expression patterns were validated using quantitative real-time PCR (qPCR) on clinical samples. Epigenetic analyses focused on promoter methylation status, and immune infiltration patterns were assessed using MethSurv, CIBERSORT and TIMER2.0. Drug sensitivity profiling was performed using the CPADS web platform.

MYBL2 was found to be significantly upregulated in UCEC tumors compared to normal tissues. Elevated MYBL2 expression correlated with advanced histologic grade and clinical stage, indicating its potential as a biomarker for disease progression. Epigenetic analysis revealed promoter hypomethylation in tumors, suggesting a regulatory mechanism driving MYBL2 overexpression. MYBL2 demonstrated dynamic interactions with the tumor immune microenvironment, including associations with immune cell infiltration patterns and co-expression with immune checkpoint molecules and chemokines. Drug sensitivity profiling highlighted differential therapeutic responses linked to MYBL2 expression levels.

This study establishes MYBL2 as a critical regulator of UCEC progression, bridging epigenetic dysregulation, immune modulation, and clinical outcomes. The findings provide a foundation for exploring MYBL2-targeted strategies in precision immunotherapy and personalized therapeutic interventions.

Locally advanced cervical cancer remains a significant therapeutic challenge, with high rates of recurrence and metastasis despite advances in chemoradiation. Immunotherapy, particularly immune checkpoint inhibitors targeting the PD-1/PD-L1 axis, has emerged as a promising strategy to enhance treatment efficacy. This review explores the integration of immunotherapy with standard chemoradiation, highlighting the potential of PD-1 inhibitors, such as pembrolizumab, in improving progression-free survival (PFS) among high-risk patients. Furthermore, the role of predictive biomarkers, including microsatellite instability (MSI) and tumor mutational burden (TMB), is examined to refine patient selection and personalize therapeutic approaches. Emerging strategies, including the use of nivolumab, ipilimumab, and maintenance immunotherapy, are also discussed. While preliminary clinical data are encouraging, further research is required to optimize treatment combinations, establish robust patient selection criteria, and enhance long-term outcomes in cervical cancer management.

Anal squamous cell carcinoma (ASCC) is a rare malignancy with an increasing incidence. Primary chemoradiotherapy (CRT) is the standard-of-care treatment for patients with localized ASCC. In the metastatic setting, trials testing immune-checkpoint inhibitor monotherapy have demonstrated outcomes similar to those of patients receiving chemotherapy. Conversely, adding the anti-PD-1 antibody retifanlimab to chemotherapy in patients with recurrent or metastatic ASCC has been shown to significantly improve outcomes. Despite considerable efforts to develop personalized therapy, treatment guidance and prognosis remain reliant on baseline clinical characteristics. An improved understanding of the molecular characteristics of ASCC has provided insights into the mechanisms that mediate tumour progression and response to CRT. For example, human papillomavirus (HPV) infection is known to have an aetiological role in most ASCCs and can modulate cellular responses to CRT via several distinct mechanisms. In this Review, we summarize emerging advances in the molecular and therapeutic landscape of ASCC, including the implementation of biomarkers for treatment guidance and translation into new therapeutic approaches, with HPV infection constituting a global determinant of both tumour biology and clinical outcome. We also discuss the rationale for combining immune-checkpoint inhibitors with CRT in patients with HPV+ tumours.

Modern clinical trials can capture tens of thousands of clinicogenomic measurements per individual. Discovering predictive biomarkers, as opposed to prognostic markers, remains challenging. To address this, we present a neural network framework based on contrastive learning-the Predictive Biomarker Modeling Framework (PBMF)-that explores potential predictive biomarkers in an automated, systematic, and unbiased manner. Applied retrospectively to real clinicogenomic datasets, particularly for immuno-oncology (IO) trials, our algorithm identifies biomarkers of IO-treated individuals who survive longer than those treated with other therapies. We demonstrate how our framework retrospectively contributes to a phase 3 clinical trial by uncovering a predictive, interpretable biomarker based solely on early study data. Patients identified with this predictive biomarker show a 15% improvement in survival risk compared to those in the original trial. The PBMF offers a general-purpose, rapid, and robust approach to inform biomarker strategy, providing actionable outcomes for clinical decision-making.

Tumor-infiltrating lymphocyte (TIL) therapy represents a breakthrough in solid tumor treatment, addressing unmet needs for patients with limited options. While its efficacy is established in advanced melanoma, TIL therapy shows early promise in non-small cell lung cancer, breast cancer, gynecological cancers, and head and neck cancers. However, challenges such as reduced T cell infiltration, lower tumor mutational burden (TMB), immunosuppressive tumor microenvironments (TME), and toxicity associated with the TIL therapy regimen hinder its broader application in these patient groups, compared with melanoma. To address these challenges, new approaches focus on the selection of tumor-reactive TIL, optimization of TIL expansion, combination of immune checkpoint inhibitors with TIL therapy to counteract immunosuppressive microenvironments, and genetic modification of TIL to enhance persistence and functionality. Larger clinical trials are essential to validate these innovations and standardize protocols. With continued advancements, TIL therapy has the potential to redefine the treatment landscape for advanced solid cancers.

Precision oncology is becoming a mainstay in the standard of care for cancer patients. Recent technological advancements have significantly lowered the cost of various tumor profiling approaches, broadening the reach of molecular diagnostics and improving patient access to precision oncology. In parallel, drug development and discovery pipelines continue to evolve, driving targeted therapeutic options forward. Yet, not all patients harboring actionable molecular alterations respond to these interventions, and existing therapies do not cover the entire spectrum of potential molecular targets. In this review, we examine the current suite of omics technologies employed in clinical settings and underscore their roles in deepening our understanding of tumor biology and optimizing patient stratification for targeted treatments. We also highlight relevant precision oncology trials and share our own experiences using multi-omics data within a molecular tumor board framework. Finally, we discuss areas for future exploration aimed at propelling precision oncology to new heights.

The Japan Association of Endocrine Surgery published the first edition of the "Clinical guidelines on the management of thyroid tumors" in 2010 and the revised edition in 2018. The guideline presented herein is the English translation of the revised third edition, issued in 2024. The aim is to enhance health outcomes for patients suffering from thyroid tumors by facilitating evidence-based shared decision-making between healthcare providers and patients, as well as standardizing the management of thyroid tumors. The focus is on adult patients with thyroid tumors, addressing clinically significant issues categorized into areas such as an overview of the diagnosis and treatment of thyroid nodules, treatment strategies by histological type, radioactive iodine therapy, treatment of advanced differentiated carcinoma, pharmacotherapy, and complications and safety management associated with thyroid surgery. Thirty-two clinical questions were established in these areas. Following a comprehensive search of the literature and systematic review to evaluate the overall evidence, we aimed to present optimal recommendations by considering the balance of benefits and harms from the patient's perspective. We integrated evidence and clinical experience to determine the "Certainty of evidence" and "Strength of recommendations". Based on these, we illustrated overall flows of care as "Clinical algorithms". Necessary background knowledge of diseases and established clinical procedures for understanding the recommendations are presented in "Notes", while information that may be clinically useful but for which evidence remains insufficient is included in "Columns", based on the current state of evidence. Finally, future challenges for the next revision are presented as "Future research questions".

Given their rarity and diversity, a fundamental understanding of the genomic underpinnings for many sarcoma subtypes is still lacking. To better define the molecular landscape of this group of diseases, we perform matched whole exome sequencing and RNA sequencing on a cohort of 1340 sarcoma tumor specimens. We identify recurrent somatic mutations and observe an increased mutational burden in metastatic vs. primary samples (p < 0.001). We observe frequent copy number alterations including whole genome doubling, with this feature being more common in metastatic tumors (p = 0.026). Estimation of immune cell abundances followed by hierarchical clustering identifies five immune subtypes ranging from low to high and we observe inferior overall survival in immune deplete clusters compared to immune enriched (p < 0.01). Interestingly, GIST predominantly form a distinct "immune intermediate" cluster that is marked by a specific enrichment for NK cells (FDR < 0.01).

In updated analyses from the phase III POSEIDON study, after a median follow-up of >5 years, tremelimumab plus durvalumab and chemotherapy (T + D + CT) showed durable long-term overall survival (OS) benefit versus CT alone in first-line metastatic non-small-cell lung cancer (mNSCLC). In this article, we report the associations of tumor mutational burden (TMB) with outcomes of D with or without T in combination with CT versus CT alone.

A total of 1013 patients with EGFR/ALK wild-type mNSCLC were randomized (1 : 1 : 1) to T + D + CT, D + CT, or CT, stratified by programmed cell death-ligand 1 (PD-L1) tumor cell (TC) expression ≥50% versus <50%, disease stage (IVA versus IVB) and histology (squamous versus nonsquamous). Patient subgroups were defined by a range of blood TMB (bTMB) values, including at a prespecified cut-off of 20 mutations (mut)/megabase (Mb) and across further subdivisions by PD-L1 TC expression ≥1% or <1% and by tissue TMB (tTMB) values.

At the primary OS data cut-off (12 March 2021), at each bTMB or tTMB cut-off, the magnitude of OS benefit appeared greater among patients in the bTMB- or tTMB-high subgroups for the T + D + CT arm versus the CT arm but was similar between subgroups for the D + CT arm versus the CT arm. Updated OS analyses in the bTMB ≥20 and <20 mut/Mb subgroups, after median follow-up of >5 years (data cut-off 24 August 2023), were similar to those obtained at the primary OS data cut-off.

First-line treatment with T (limited course) plus D (until progression) and four cycles of CT consistently improved clinical outcomes versus CT alone in both bTMB-high and -low subgroups, and also in both high and low tTMB subgroups, in patients with mNSCLC. Benefit appeared greater in the TMB-high versus TMB-low subgroups; the addition of anti-cytotoxic T lymphocyte-associated antigen-4 to anti-PD-L1 and CT seemed to increase the magnitude of this difference.

Utilizing real-world data from Japan's C-CAT clinicogenomic repository, our study demonstrates a significant shift in cancer management through cancer genomic profiling (CGP) tests. The aim of this study is assessing the prevalence of cross-organ targeted genetic alterations and exploring the differences in treatment responses among cancer patients who underwent CGP tests.

Analyzing data from 60,256 patients in the C-CAT repository, we documented the prevalence of FDA-approved biomarkers, cross-organ genetic alterations, and treatment outcomes for tissue-agnostic therapies from June 2019 to December 2023.

Biomarkers including RET rearrangement, BRAFV600E mutation, and NTRK rearrangement showed varied therapeutic responses, underscoring the need for universal CGP testing to optimize patient outcomes. Notably, our findings highlight variations in response across different age groups, suggesting the potential for age-specific treatment strategies. Comparisons with the AACR Project GENIE database revealed broader implications for the global genomic landscape.

This study emphasizes the crucial role of clinicogenomic repositories in advancing precision oncology across diverse populations, underscoring the utility of integrating clinical and genomic data in national repositories.

High tumor mutational burden (TMB-H) is an established biomarker for a favorable response to immune checkpoint inhibitors. However, tumor mutational burden (TMB) in invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) has not been sufficiently investigated.

We collected data of patients with ILC or IDC from the Center for Cancer Genomics and Advanced Therapeutics database between June 2019 and August 2023. Furthermore, we examined the clinicopathological factors and TMB status.

Patients with ILC (n = 170) had a median TMB score of 4.00 mut/Mb (interquartile range, 2.00-7.14 mut/Mb), whereas those with IDC (n = 2598) had a score of 3.90 mut/Mb (2.00-6.00 mut/Mb). TMB-H was more common in patients with ILC than in those with IDC (18.2% vs. 10.1%, P < 0.001), particularly in the ER+ /HER2- subtype. Multivariate analysis revealed that the pathological diagnosis of ILC (P = 0.006), tissue samples collected from metastatic sites (P < 0.001), and older age (50 years, P < 0.001) were independent factors for TMB-H.

Patients with ILC were more likely to have TMB-H than those with IDC. The findings of this study would be invaluable in selecting treatment strategies for patients with ILC.

This study aimed to reveal the gene alteration and tumor mutation burden (TMB) statuses of vulvar and vaginal malignant tumors in Japan.

We investigated the cancer genomic profiling (CGP) data of 79 patients with vulvar and vaginal cancers. These data were obtained from the Center for Cancer Genomics and Advanced Therapeutics (C-CAT).

None of the patients had high microsatellite instability. Although 21.9% of the patients with vulvar and vaginal squamous cell carcinoma (SCC) had high TMB, those with other histological types did not. The top single-nucleotide variants (SNVs) in SCC were TERT, TP53, CDKN2A, KMT2D, and NOTCH1. The frequencies of ATRX and PBRM1 were significantly higher in TMB-high SCC than in non-TMB-high SCC.

SCC of the vulva and vagina is expected to have high TMB, and gene alteration status differed between TMB-high and non-TMB-high groups.