Identification of molecular subtypes, prognostic status and immunotherapy response in cervical cancer based on angiogenic signature genes.

Background: Cervical cancer, as one of the most common malignancies in women, is closely related to the mechanism of angiogenesis, which needs further exploration. Methods: The squamous cell carcinoma of the cervix and cervical adenocarcinoma (CESC) data from The Cancer Genome Atlas (TCGA) database. CESC subtypes based on 48 angiogenesis-related genes were identified using consistent cluster analysis, and the limma package were adopted to screen the differentially expressed genes (DEGs) associated with prognosis. Further compress the DEGs through univariate and Least Absolute Shrinkage and Selection Operator (LASSO) COX analysis to identify the key genes. Calculate immune scores using the GSVA package and predict immunotherapy response with TIDE. For in vitro analysis, the expressions of these key genes were additionally tested via reverse-transcription quantitative PCR, and the migration and invasion of Hela cells were determined in scratch and transwell assays, respectively. Results: 3 CESC subtypes were identified, with the best survival advantage in the C2 subtype and the worst in C1 subtype. A risk model was established utilizing seven key genes (MMP3, DLL4, CAP2, PDIA6, TCN2, PAPSS2, and VCAM1), showcases an Area Under the Curve (AUC) exceeding 0.7, underlining its robust performance. The risk score model showed a trend of poorer survival for patients in the high-risk score group and good agreement across different datasets. A nomogram was constructed, and calibration curves indicated robust predictive performance. Immunological analysis revealed heightened sensitivity to immunotherapy in the low-risk group. Besides, the elevated expressions of all 7 genes were seen in Hela cells, and the specific target-mediated DLL4 knockdown diminished the migration and invasion of Hela cells in vitro. Conclusion: This research provides fresh insights and a valuable tool to guide therapeutic decision-making for CESC.

Clarifying new molecular subtyping and precise treatment of melanoma based on disulfidptosis-related lncRNA signature.

Disulfidptosis, the newest form of programmed cell death, is closely associated with the immune microenvironment of cancer cells. Long non-coding RNA (lncRNA) has also been found to play a crucial role in melanoma. However, the role of disulfidptosis-related lncRNA in melanoma remains unclear. Through bioinformatic analysis of the transcriptional, clinical, and pathological data from the TCGA-SKCM (The Cancer Genome Atlas-Skin cutaneous melanoma) database, we established a 2-Disulfidptosis-related lncRNA (DRL) prognostic model and a novel molecular subtype for melanoma. The survival and ROC curves of the 2-DRL prognostic model demonstrated its strong efficacy in predicting the prognosis of melanoma. The high-risk group of melanoma exhibited a significant decrease in ESTIMATEScore, ImmuneScore, and StromalScore, indicative of pronounced immune suppression and exhaustion. Subgroup C2 of melanoma displayed an immune-activated state, while subgroups C1 and C3 showed immune suppression and exhaustion, potentially leading to poorer prognosis. Subgroup C1 demonstrated better sensitivity to Zoledronate, UMI-77, Nilotinib, and Cytarabine. Subgroup C2 exhibited greater sensitivity to Ribociclib, XAV939, Topotecan, and Ruxolitinib. Subgroup C3 showed higher sensitivity to VX-11e, Ulixertinib, Trametinib, and Afatinib. This study revealed the immune microenvironment status and targeted drug sensitivity in melanoma patients with different risk scores and molecular subtypes, offering valuable guidance for clinical treatment and identifying significant DRL targets for future in-depth research.

MTAP protein status is highly concordant with CDKN2A fluorescent in situ hybridization and allows stratification of the luminal subtype in muscle-invasive bladder cancer.

AIMS: Loss of heterozygosity in chromosome 9p21, common in urothelial carcinoma (UC), typically involves deletion of CDKN2A and MTAP genes. MTAP loss is emerging as a promising therapeutic target and predictive biomarker in UC. This single-centrre retrospective study examined the incidence of CDKN2A deletions and MTAP loss in muscle-invasive bladder cancer (MIBC) and metastatic urothelial carcinoma (mUC), investigating their correlations with clinical, pathological, and genomic features, as well as patient outcomes. METHODS: Fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) were performed on 302 MIBC specimens and 63 biopsy-proven metachronous urothelial metastases to assess CDKN2A deletions and MTAP protein expression. RESULTS: CDKN2A homozygous deletion (HD), identified in 30.3% of MIBCs, and MTAP loss, found in 28.8% of MIBCs, were both significantly associated with the luminal-URO subtype, FGFR3 mutations, and normal/wildtype p53 IHC (P < 0.05). Loss of MTAP expression was significantly correlated with CDKN2A HD, with 84.0% sensitivity, 92.3% negative predictive value (NPV), 96.3% specificity, and 91.9% positive predictive value (PPV). MTAP expression was 100% concordant between primary tumours and nodal metastases. Patients with MTAP loss had a higher incidence of visceral metastases (50%) compared to bone/soft tissue (35.7%) and nodes (14.3%). Mean progression-free survival and overall survival were shorter for patients with MTAP loss, although not statistically significant. CONCLUSION: Our findings highlight CDKN2A HD and MTAP loss as prevalent genetic alterations in MIBC and mUC, particularly within the luminal-URO subtype and FGFR3-mutated, p53-normal/wildtype tumours. MTAP IHC can serve as a surrogate marker for 9p21.3 HD, highlighting its clinical relevance and potential as a therapeutic target and predictive biomarker in MIBC.

Redefining YAP1 in small cell lung cancer: shifting from a dominant subtype marker to a favorable prognostic indicator.

Background: Molecular and transcription factor subtyping were recently introduced to identify patients with unique clinical features in small cell lung cancer (SCLC). However, its prognostic relevance is yet to be established. This study aims to investigate the clinical implications and prognostic significance of transcription factor subtyping in SCLC using immunohistochemistry. Methods: One hundred and ninety consecutive SCLC patients treated with platinum-based chemotherapy at a single institution were retrospectively reviewed. Expression of ASCL1, NeuroD1, POU2F3, and YAP1 was assessed by immunohistochemical staining and applied to determine the transcription factor subtype of each case. Results: The association among transcription factors was not entirely mutually exclusive. YAP1 expression was the most significant prognostic indicator compared with other transcription factors or their related subtypes. Among patients with limited-stage disease (LD), complete response (CR) rates were 46.2% and 22.4% in the YAP1-positive and YAP1-negative groups, respectively. The median duration of response among patients who achieved CR was 64.8 and 36.4 months in the YAP1-positive and YAP1-negative groups, respectively (P=0.06). Median overall survival (OS) in LD was 35.6 and 16.9 months in the YAP1-positive and YAP1-negative groups, respectively (P=0.03). In extensive-stage disease (ED), the median OS was 11.3 months for the YAP1-positive group and 11 months for the YAP1-negative group (P=0.03). Conclusions: Positive expression of YAP1 can be associated with durable CR and favorable survival outcomes in patients with SCLC, especially in LD.

Clinicopathological characteristics of endometrial carcinoma with different molecular subtypes and their correlation with lymph node metastasis.

Endometrial carcinoma (EC) is one of the three major malignancies of the female reproductive organs. With intense research of tumor molecular mechanisms and development of precision medicine in recent years, the traditional pathomorphological classification fails to meet the needs of clinical diagnosis and treatment for EC. This study aims to analyze the correlation of different Proactive Molecular Risk Classifier for Endometrial Cancer molecular subtypes with lymph node metastasis (LNM) and other clinical features in EC. 120 treatment-naive EC patients with surgery were enrolled in this study. The molecular subtypes of these patients were classified as follows by Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE) molecular subtyping: mismatch repair deficiency (MMRd) in 22 cases (18.33%), polymerase epsilon exonuclease domain mutation (POLE EDM) in 2 cases (1.67%), p53 wild-type (p53-wt) in 64 cases (53.33%), and p53 abnormal (p53-abn) in 32 cases (26.67%). The clinicopathological features of 120 patients were retrospectively analyzed. Statistical significance was identified among the four molecular subtypes in terms of histological classification, International Federation of Gynecology and Obstetrics (FIGO) staging, pathological grading, and LNM. Among the enrolled cases, 26 had LNM and 94 had no lymph node involvement. According to the multivariate Logistic regression analysis, p53 wt (P=0.008, OR=0.078, 95% CI: 0.012-0.510) was a protective factor for LNM in EC patients, while poorly differentiated histology (P=0.001, OR=15.137, 95% CI: 3.013-76.044) was a risk factor. ProMisE classification system, being more objective and reproducible, can provide an important reference for preoperative decision-making. The patients with p53 wt by ProMisE had a low risk of LNM in preoperative diagnostic curettage specimens, while there was a higher risk of LNM among the patients with poorly differentiated EC.

The clinical utility of next generation sequencing in endometrial cancer: focusing on molecular subtyping and lynch syndrome.

Objective: To investigate the clinical utility of Next Generation Sequencing (NGS) in molecular typing of endometrial carcinoma and its combined screening for Lynch Syndrome (LS). Methods: 90 patients diagnosed with endometrial carcinoma (EC) and receiving treatment at the Third Affiliated Hospital of Zhengzhou University between March 2022 and December 2023 were included in this study. Molecular typing and germline evaluation for LS were conducted using NGS on the Illumina platform. A retrospective analysis was performed to examine the clinical pathological characteristics, molecular mutation spectrum, and LS screening outcomes among patients with four distinct molecular subtyping categories. Results: Among the 90 cases of EC, 11 cases (12.2%) of POLE mut type, 19 cases (21.1%) of MMRd type, 6 cases (6.7%) of p53 abn type, and 54 cases (60%) of NSMP type were detected, with detailed analysis of their respective molecular characteristics. LS screening identified 9 cases (10%) of pathogenic germline mutations in MMR genes, including 3 cases of MLH1 germline mutations, 2 cases of PMS2, 2 of MSH2, and 2 of MSH6. Of the 9 LS patients, 7 were MMRd type and 2 NSMP type, with 7 cases showing abnormal MMR protein expression. Additionally, 6 cases with germline variants of uncertain significance in MMR genes were detected, including 2 MLH1, 1 MSH6, 2 MSH6, 1 PMS2, and 1 EPCAM. Conclusion: NGS enables precise molecular typing of endometrial carcinoma through the identification of mutations in the POLE, TP53, and MMR genes. Conducting germline mutation testing for MMR genes in all patients with endometrial carcinoma can effectively prevent instances of overlooked LS diagnoses. Nevertheless, the extensive expenses associated with NGS necessitate additional validation and investigation before its clinical implementation can be fully endorsed.

Comprehensive multi-omics profiling identifies novel molecular subtypes of pancreatic ductal adenocarcinoma.

Pancreatic cancer, a highly fatal malignancy, is predicted to rank as the second leading cause of cancer-related death in the next decade. This highlights the urgent need for new insights into personalized diagnosis and treatment. Although molecular subtypes of pancreatic cancer were well established in genomics and transcriptomics, few known molecular classifications are translated to guide clinical strategies and require a paradigm shift. Notably, chronically developing and continuously improving high-throughput technologies and systems serve as an important driving force to further portray the molecular landscape of pancreatic cancer in terms of epigenomics, proteomics, metabonomics, and metagenomics. Therefore, a more comprehensive understanding of molecular classifications at multiple levels using an integrated multi-omics approach holds great promise to exploit more potential therapeutic options. In this review, we recapitulated the molecular spectrum from different omics levels, discussed various subtypes on multi-omics means to move one step forward towards bench-to-beside translation of pancreatic cancer with clinical impact, and proposed some methodological and scientific challenges in store.

Updates in Molecular Profiling of Pancreatic Ductal Adenocarcinoma.

Outcomes from pancreatic ductal adenocarcinoma (PDAC) remain poor and better methods of prognostication and therapeutic approaches are needed. Recent advances in cancer genomics have led to the development of molecular subtypes of PDAC associated with clinical outcomes. Current evidence also suggests that the subtypes have differential response to first-line chemotherapy regimens. PDAC is also characterized by different stroma and immune environments. Further work is needed to confirm the utility of these subtypes to predicting response to different systemic therapies.

Proteomic and phosphoproteomic landscape of localized prostate cancer unveils distinct molecular subtypes and insights into precision therapeutics.

Building upon our previous investigation of genomic, epigenomic, and transcriptomic profiles of prostate cancer in China, we conducted a comprehensive analysis of proteomic and phosphoproteomic profiles of 82 tumor tissues and matched adjacent normal tissues from 41 Chinese patients with localized prostate cancer. We identified three distinct proteomic subtypes with significant difference in both molecular features and clinical prognosis. Notably, these proteomic subtypes exhibited a parallel degree of heterogeneity in the phosphoproteome, featuring unique metabolism, proliferation, and immune infiltration characteristics. We further demonstrated that a combination of proteins and phosphosites serves as the most effective biomarkers in prostate cancer to predict biochemical recurrence. Through an integrated multiomics analysis, we revealed mechanistic differences underlying different proteomic subtypes and highlighted the potential significance of Serine/arginine-rich splicing factor 1 (SRSF1) phosphorylation in promoting the malignant characteristics of prostate cancer cells. Our multiomics data provide valuable resources for understanding the molecular mechanisms of prostate cancer within the Chinese population, which have the potential to inform the development of personalized treatment strategies and enhance prognostic analyses for prostate cancer patients.

Patient subtyping analysis of baseline multi-omic data reveals distinct pre-immune states associated with antibody response to seasonal influenza vaccination.

Understanding the molecular mechanisms underpinning diverse vaccination responses is critical for developing efficient vaccines. Molecular subtyping can offer insights into heterogeneous nature of responses and aid in vaccine design. We analyzed multi-omic data from 62 haemagglutinin seasonal influenza vaccine recipients (2019-2020), including transcriptomics, proteomics, glycomics, and metabolomics data collected pre-vaccination. We performed a subtyping analysis on the integrated data revealing five subtypes with distinct molecular signatures. These subtypes differed in the expression of pre-existing adaptive or innate immunity signatures, which were linked to significant variation in baseline immunoglobulin A (IgA) and hemagglutination inhibition (HAI) titer levels. It is worth noting that these differences persisted through day 28 post-vaccination, indicating the effect of initial immune state on vaccination response. These findings highlight the significance of interpersonal variation in baseline immune status as a crucial factor in determining the effectiveness of seasonal vaccines. Ultimately, incorporating molecular profiling could enable personalized vaccine optimization.

Identification of PANoptosis-relevant subgroups and predicting signature to evaluate the prognosis and immune landscape of patients with biliary tract cancer.

BACKGROUND: This study conducted molecular subtyping of biliary tract cancer patients based on 19 PANoptosis-related gene signatures. METHODS: Through consensus clustering, patients were categorized into two subtypes, A and B. By integrating multi-omics data and clinical information from different cohorts, we elucidated the association between different subtypes of biliary tract cancer and patient prognosis, which correlated with the immune infiltration characteristics of patients. RESULTS: LASSO regression analysis was performed on the 19 gene signatures, and we constructed and validated a 9-gene risk score prognostic model that accurately predicts the overall survival rate of different biliary tract cancer patients. Additionally, we developed a predictive nomogram demonstrating the clinical utility and robustness of our model. Further analysis of the risk score-based immune landscape highlighted potential associations with immune cell infiltration, chemotherapy, and immune therapy response. CONCLUSION: Our study provides valuable insights into personalized treatment strategies for biliary tract cancer, which are crucial for improving patient prognosis and guiding treatment decisions in clinical practice.

Comprehensive Transcriptome Analysis Expands lncRNA Functional Profiles in Breast Cancer.

Breast cancer is a heterogeneous disease that arises as a multi-stage process involving multiple cell types. Patients diagnosed with the same clinical stage and pathological classification may have different prognoses and therapeutic responses due to alterations in molecular genetics. As an essential marker for the molecular subtyping of breast cancer, long non-coding RNAs (lncRNAs) play a crucial role in gene expression regulation, cell differentiation, and the maintenance of genomic stability. Here, we developed a modular framework for lncRNA identification and applied it to a breast cancer cohort to identify novel lncRNAs not previously annotated. To investigate the potential biological function, regulatory mechanisms, and clinical relevance of the novel lncRNAs, we elucidated the genomic and chromatin features of these lncRNAs, along with the associated protein-coding genes and putative enhancers involved in the breast cancer regulatory networks. Furthermore, we uncovered that the expression patterns of novel and annotated lncRNAs identified in breast cancer were related to the hormone response in the PAM50 subtyping criterion, as well as the immune response and progression states of breast cancer across different immune cells and immune checkpoint genes. Collectively, the comprehensive identification and functional analysis of lncRNAs revealed that these lncRNAs play an essential role in breast cancer by altering gene expression and participating in the regulatory networks, contributing to a better insight into breast cancer heterogeneity and potential avenues for therapeutic intervention.

Similar genetic profile in early and late stage urothelial tract cancer.

INTRODUCTION: Urothelial tract cancer (UTC) ranks as the tenth most prevalent cancer and holds the seventh position in terms of mortality worldwide. Despite its prevalence and mortality ranking, there are still gaps in the knowledge of the mutational landscape in patients with advanced disease who have limited therapeutic options after multiple lines of prior treatment. This study compares the genomic and transcriptomic landscape, and targeted treatment options between metastatic UTC (mUTC) patients treated with multiple lines of therapy compared to newly diagnosed, untreated Muscle Invasive Bladder Cancer (MIBC). METHODS: We compared genomic and clinical data from two cohorts: mUTC patients who received multiple lines of therapy and were referred to the Copenhagen Prospective Personalized Oncology (CoPPO) project at Rigshospitalet, University of Copenhagen. Data for MIBC UTC patients were acquired from the Cancer Genome Atlas Bladder Cancer (TCGA BLCA) cohort. Biopsies in CoPPO were performed at the time of enrollment. 523 highly important cancer-related genes (TrueSight Oncology-500 targeted sequencing panel) were used from both cohorts for comparative analysis. Analyses included RNA count data to compare predicted molecular subtypes in each cohort separately. RESULTS: Patients from the CoPPO cohort had a lower median age at first-line treatment than the TCGA BLCA cohort, with no significant gender disparity. The predominant histology was urothelial cell carcinoma in both cohorts. Genomic analysis revealed no significant difference between the top mutated genes in the two cohorts, specifically looking into DNA damage repair genes. Molecular subtyping indicated a higher frequency of neuroendocrine differentiation in the CoPPO cohort. 13% of patients in the CoPPO cohort received targeted therapy based on genomic findings, and 16% received non-targeted treatment, totaling 29% receiving CoPPO treatment (9 patients). The remaining 71% received best supportive care. Kaplan-Meier analysis showed a non-significant survival benefit for the intervention group in the CoPPO cohort. CONCLUSION: When focusing on 523 highly relevant cancer genes, the mutational profile of mUTC patients who have undergone numerous treatment lines resembles that of newly diagnosed MIBC. These alterations can be targeted, indicating the potential advantage of early genomic testing for personalized treatment within clinical trials.

Evolving treatment landscape in thymic epithelial tumors: From mechanism to therapy.

Thymic epithelial tumors (TETs) are rare neoplasms of the anterior mediastinum that arise from thymic epithelial cells. Although surgery is the preferred treatment for resectable TETs, the options for unresectable or recurrent advanced-stage TETs are limited beyond platinum-based chemotherapy. The evolving landscape of TET treatments is marked by significant advancements in targeted therapies and immunotherapies, particularly with anti-angiogenic agents and immune checkpoint inhibitors (ICIs). While monotherapies demonstrated certain efficacy, the development of combination strategies is vital for improving patient outcomes. This review consolidates progress in anti-angiogenic therapies and ICIs, emphasizing the evolution of combination therapies of TETs. Furtherly, we particularly discuss new first-line strategies based on these advancements and emphasizes exploring novel treatments like antibody-drug conjugates, immunomodulatory drugs and cytokine-based agents for TETs. Mechanistically, the molecular features of TETs integrated with clinical diagnosis and targeted therapy, and immunophenotyping of TETs along with its impact on the efficacy and safety of immunotherapy are discussed. Thus, this review systemizes the development in the treatment landscape of TETs, integrating the corresponding molecular and immune mechanisms, aiming to provide new references for the treatment of TETs.

Methods in DNA methylation array dataset analysis: A review.

Understanding the intricate relationships between gene expression levels and epigenetic modifications in a genome is crucial to comprehending the pathogenic mechanisms of many diseases. With the advancement of DNA Methylome Profiling techniques, the emphasis on identifying Differentially Methylated Regions (DMRs/DMGs) has become crucial for biomarker discovery, offering new insights into the etiology of illnesses. This review surveys the current state of computational tools/algorithms for the analysis of microarray-based DNA methylation profiling datasets, focusing on key concepts underlying the diagnostic/prognostic CpG site extraction. It addresses methodological frameworks, algorithms, and pipelines employed by various authors, serving as a roadmap to address challenges and understand changing trends in the methodologies for analyzing array-based DNA methylation profiling datasets derived from diseased genomes. Additionally, it highlights the importance of integrating gene expression and methylation datasets for accurate biomarker identification, explores prognostic prediction models, and discusses molecular subtyping for disease classification. The review also emphasizes the contributions of machine learning, neural networks, and data mining to enhance diagnostic workflow development, thereby improving accuracy, precision, and robustness.

Molecular classification and biomarkers of outcome with immunotherapy in extensive-stage small-cell lung cancer: analyses of the CASPIAN phase 3 study.

BACKGROUND: We explored potential predictive biomarkers of immunotherapy response in patients with extensive-stage small-cell lung cancer (ES-SCLC) treated with durvalumab (D) + tremelimumab (T) + etoposide-platinum (EP), D + EP, or EP in the randomized phase 3 CASPIAN trial. METHODS: 805 treatment-naïve patients with ES-SCLC were randomized (1:1:1) to receive D + T + EP, D + EP, or EP. The primary endpoint was overall survival (OS). Patients were required to provide an archived tumor tissue block (or ≥ 15 newly cut unstained slides) at screening, if these samples existed. After assessment for programmed cell death ligand-1 expression and tissue tumor mutational burden, residual tissue was used for additional molecular profiling including by RNA sequencing and immunohistochemistry. RESULTS: In 182 patients with transcriptional molecular subtyping, OS with D ± T + EP was numerically highest in the SCLC-inflamed subtype (n = 10, median 24.0 months). Patients derived benefit from immunotherapy across subtypes; thus, additional biomarkers were investigated. OS benefit with D ± T + EP versus EP was greater with high versus low CD8A expression/CD8 cell density by immunohistochemistry, but with no additional benefit with D + T + EP versus D + EP. OS benefit with D + T + EP versus D + EP was associated with high expression of CD4 (median 25.9 vs. 11.4 months) and antigen-presenting and processing machinery (25.9 vs. 14.6 months) and MHC I and II (23.6 vs. 17.3 months) gene signatures, and with higher MHC I expression by immunohistochemistry. CONCLUSIONS: These findings demonstrate the tumor microenvironment is important in mediating better outcomes with D ± T + EP in ES-SCLC, with canonical immune markers associated with hypothesized immunotherapy mechanisms of action defining patient subsets that respond to D ± T. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03043872.

Subtype-WGME enables whole-genome-wide multi-omics cancer subtyping.

We present an innovative strategy for integrating whole-genome-wide multi-omics data, which facilitates adaptive amalgamation by leveraging hidden layer features derived from high-dimensional omics data through a multi-task encoder. Empirical evaluations on eight benchmark cancer datasets substantiated that our proposed framework outstripped the comparative algorithms in cancer subtyping, delivering superior subtyping outcomes. Building upon these subtyping results, we establish a robust pipeline for identifying whole-genome-wide biomarkers, unearthing 195 significant biomarkers. Furthermore, we conduct an exhaustive analysis to assess the importance of each omic and non-coding region features at the whole-genome-wide level during cancer subtyping. Our investigation shows that both omics and non-coding region features substantially impact cancer development and survival prognosis. This study emphasizes the potential and practical implications of integrating genome-wide data in cancer research, demonstrating the potency of comprehensive genomic characterization. Additionally, our findings offer insightful perspectives for multi-omics analysis employing deep learning methodologies.

Therapeutic vulnerabilities in triple negative breast cancer: Stem-like traits explored within molecular classification.

Triple Negative Breast Cancer (TNBC) is the most aggressive type of breast cancer (BC). Despite advances in the clinical management of TNBC, recurrence-related mortality remains a challenge. The stem-like phenotype of TNBC plays a significant role in the persistence of minimal disease residue after therapy. Individuals exhibiting stem-like characteristics are particularly prone to inducing malignant relapse accompanied by strong resistance. Therefore, stem-like traits have been broadly proposed as therapeutic vulnerabilities to treat TNBC and reduce recurrence. However, heterogeneity within TNBC often generally restricts the stability of the therapeutic efficacy. To understand the heterogeneity and manage TNBC more precisely, multiple TNBC subtyping categories have been reported, providing the basis for profile-according therapeutic regimens. To provide more insight into targeting stem-like traits to ablate TNBC and reduce recurrence in the context of heterogeneity, this paper reviewed the molecular subtyping of TNBC, identified the consensus subtypes with distinct stem-like phenotypes, characterized the stemness hierarchy of TNBC, outlined the biological models for stem-like TNBC subtypes, summarized the therapeutic vulnerabilities in stem-like traits of the subtypes, and proposed potential therapeutic regimens targeting stem-like characteristics to improve TNBC prognosis.

Integrated Exploration of Epigenetic Dysregulation Reveals a Stemness/EMT Subtype and MMP12 Linked to the Progression and Prognosis in Hepatocellular Carcinoma.

Epigenetic dysregulation drives aberrant transcriptional programs playing a critical role in hepatocellular carcinoma (HCC), which may provide novel insights into the heterogeneity of HCC. This study performed an integrated exploration on the epigenetic dysregulation of miRNA and methylation. We discovered and validated three patterns endowed with gene-related transcriptional traits and clinical outcomes. Specially, a stemness/epithelial-mesenchymal transition (EMT) subtype was featured by immune exhaustion and the worst prognosis. Besides, MMP12, a characteristic gene, was highly expressed in the stemness/EMT subtype, which was verified as a pivotal regulator linked to the unfavorable prognosis and further proven to promote tumor proliferation, invasion, and metastasis in vitro experiments. Proteomic analysis by mass spectrometry sequencing also indicated that the overexpression of MMP12 was significantly associated with cell proliferation and adhesion. Taken together, this study unveils innovative insights into epigenetic dysregulation and identifies a stemness/EMT subtype-specific gene, MMP12, correlated with the progression and prognosis of HCC.

Tumor immune dysfunction and exclusion subtypes in bladder cancer and pan-cancer: a novel molecular subtyping strategy and immunotherapeutic prediction model.

BACKGROUND: Molecular subtyping is expected to enable precise treatment. However, reliable subtyping strategies for clinical application remains defective and controversial. Given the significance of tumor immune dysfunction and exclusion (TIDE), we aimed to develop a novel TIDE-based subtyping strategy to guide personalized immunotherapy in the bladder cancer (BC). METHODS: Transcriptome data of BC was used to evaluate the heterogeneity and the status of TIDE patterns. Subsequently, consensus clustering was applied to classify BC patients based on TIDE marker-genes. Patients' clinicopathological, molecular features and signaling pathways of the different TIDE subtypes were well characterized. We also utilize the deconvolution algorithms to analyze the tumor microenvironment, and further explore the sensitivity and mechanisms of each subtype to immunotherapy. Furthermore, BC patient clinical information, real-world BC samples and urine samples were collected for the validation of our findings, which were used for RNA-seq analysis, H&E staining, immunohistochemistry and immunofluorescence staining, and enzyme-linked immunosorbent assay. Finally, we also explored the conservation of our novel TIDE subtypes in pan-cancers. RESULTS: We identified 69 TIDE biomarker genes and classified BC samples into three subtypes using consensus clustering. Subtype I showed the lowest TIDE status and malignancy with the best prognosis and highest sensitivity to immune checkpoint blockade (ICB) treatment, which was enriched of metabolic related signaling pathways. Subtype III represented the highest TIDE status and malignancy with the poorest prognosis and resistance to ICB treatment, resulting from its inhibitory immune microenvironment and T cell terminal exhaustion. Subtype II was in a transitional state with intermediate TIDE level, malignancy, and prognosis. We further confirmed the existence and characteristics of our novel TIDE subtypes using real-world BC samples and collected patient clinical data. This subtyping method was proved to be more efficient than previous known methods in identifying non-responders to immunotherapy. We also propose that combining our TIDE subtypes with known biomarkers can potentially improve the sensitivity and specificity of these biomarkers. Moreover, besides guiding ICB treatment, this classification approach can assist in selecting the frontline or recommended drugs. Finally, we confirmed that the TIDE subtypes are conserved across the pan-tumors. CONCLUSIONS: Our novel TIDE-based subtyping method can serve as a powerful clinical tool for BC and pan-cancer patients, and potentially guiding personalized therapy decisions for selecting potential beneficiaries and excluding resistant patients of ICB therapy.