Cancer Molecular Subtypes Research Articles

Prognostic effect of immunohistochemically determined molecular subtypes in gastric cancer

IntroductionGastric cancer is the fifth most common cancer worldwide and the fourth most common cause of cancer-related death. Two molecular subtyping classifications were recently introduced: The Cancer Genome Atlas (TCGA) and the Asian Cancer Research Group (ACRG) classifications.MethodsWe classified a cohort of 283 gastric cancer patients undergoing surgery at Helsinki University Hospital between 2000 and 2009. We constructed a tumour tissue microarray immunostained for the following markers: microsatellite instability (MSI) markers MSH2, MSH6, MLH1, and PMS2; p53; E-cadherin; and EBERISH.ResultsIn the univariate survival analysis for disease-specific survival, the Epstein–Barr virus (EBV) -positive subtype exhibited the worst prognosis with a hazard ratio (HR) of 2.49 (95% confidence interval [CI] 1.19–5.25, p = 0.016) compared with the most benign subtype, chromosomal instability (CIN). Using TCGA’s classification, the genetically stable (GS) and MSI subtypes exhibited a worse survival compared with CIN (HR 1.73 [95% CI 1.15–2.60], p = 0.009 and HR 1.74 [95% CI 1.06–2.84], p = 0.027, respectively). Using the ACRG classification, the p53 aberrant subtype exhibited the best prognosis, whereas wild-type p53, MSI, and the epithelial–mesenchymal transition (EMT) subtypes exhibited poorer prognoses (EMT: HR 1.90 [95% CI 1.30–2.77], p < 0.001) when compared with aberrant p53.ConclusionsImmunohistochemical analysis can identify prognostically different molecular subtypes of gastric cancer. The method is inexpensive and fast, yet reveals significant information for clinical decision-making. However, our study did not find that either molecular subtyping performed better than the other classification. Thus, further development of the most optimal grouping of different molecular subtypes is still needed.

The molecular subtypes of small cell lung cancer defined by key transcription factors and their clinical significance

BackgroundLung cancer, a prevalent and deadly malignancy, is classified into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). SCLC is further subdivided into four molecular subtypes—SCLC-A, SCLC-N, SCLC-P, and SCLC-I—based on key transcription factor expression. MethodsImmunohistochemistry (IHC) was used to assess ASCL1, NEUROD1, and POU2F3 expression in tumor tissues. The H-Score quantified these results. Clinical characteristics, overall survival (OS), progression-free survival (PFS), and treatment responses were analyzed by subtype, and sensitivity to different treatments was assessed. Risk factors were identified through univariate and multivariate analyses. ResultsIHC and H-Score analysis showed that POU2F3 expression was mutually exclusive with ASCL1 or NEUROD1. Subtype distribution was as follows: SCLC-A (40 %), SCLC-N (33 %), SCLC-P (7 %), and SCLC-I (20 %). There were no significant differences in baseline characteristics, OS (p = 0.829), or PFS (p = 0.924) among subtypes. However, the SCLC-I subtype showed a trend toward improved outcomes with platinum-based doublet chemotherapy plus immune checkpoint inhibitors. Multivariate COX regression identified M stage (HR: 1.72, 95 % CI: 1.13–2.63, p = 0.012) and bone metastasis at diagnosis (HR: 1.58, 95 % CI: 1.02–2.43, p = 0.040) as independent risk factors. ConclusionThis study confirmed the SCLC subtyping based on key transcription factors. While no significant differences in OS and PFS among subtypes were found, the SCLC-I subtype showed potential benefit from platinum-based chemotherapy combined with immune checkpoint inhibitors. M stage and bone metastasis at diagnosis were identified as independent risk factors for SCLC.

RB Loss in p53 Abnormal Endometrial Carcinoma: Histological and Clinicopathological Correlates

Of the four molecular subtypes of endometrial cancer (EC), p53-abnormal (p53abn) EC is associated with abundant copy number alterations (CNAs) and the worst clinical outcome. Patients with p53abn EC have the highest risk of disease recurrence and death, independent of tumor grade and histologic subtype. Currently, all invasive p53abn ECs are considered high risk, and no prognostic biomarkers have yet been found that can aid in clinical management. Here, we aimed to test whether loss of retinoblastoma protein (RB) expression using immunohistochemistry (IHC) has potential for prognostic refinement of p53abn EC. A large cohort of 227 p53abn ECs collected from the PORTEC-1/2/3 clinical trials and the MST cohort study was investigated, and RB loss was identified in 7.0% (n=16/227). RB-lost p53abn ECs were predominantly high-grade endometrioid ECs (n=6, 37.5%) and carcinosarcomas with endometrioid-type epithelial component (n=5, 31.3%). Histologically, RB-lost p53abn EC were typified by high grade nuclear atypia (n=16, 100%), predominantly solid growth pattern (n=15/16, 93.8%), and polypoid growth (n=9/16, 56.3%). Copy number loss involving the RB1 locus was identified in the majority of RB-lost p53abn EC (n=13/14, 92.9%), explaining the loss of RB expression. Comparative analysis also showed that RB-lost p53abn EC were diagnosed at earlier stages than RB-retained p53abn EC (p=0.014). Interestingly, RB-lost p53abn EC showed prolonged time to overall recurrence (p=0.038), even within stage I alone (p=0.040). These findings highlight distinct morphomolecular features in RB-lost p53abn EC and confirm the utility of RB IHC as a surrogate for molecular RB1 alterations. This is the first study to show the potential use of RB in prognostic refinement of p53abn EC, although validation is warranted.

Molecular subtypes of endometrioid endometrial cancer predict rates of lymph node and ovarian metastasis at the time of surgical staging

Molecular subtypes of endometrioid endometrial cancer predict rates of lymph node and ovarian metastasis at the time of surgical staging

A fully next-generation sequencing-based method of classifying molecular subtypes of endometrial cancer retains prognostic value and highlights racial disparities in disease-specific survival

A fully next-generation sequencing-based method of classifying molecular subtypes of endometrial cancer retains prognostic value and highlights racial disparities in disease-specific survival

The impact of physical activity on progression-free and overall survival in metastatic breast cancer based on molecular subtype

BackgroundAlthough adequate physical activity has been shown to be beneficial in early breast cancer, evidence in metastatic breast cancer is sparse and contradictory, which could be related to distinct effects of physical activity on the different molecular cancer subtypes. Therefore, we here evaluated the effect of physical activity on progression-free and overall survival (PFS, OS) in metastatic breast cancer, specifically looking at molecular subtypes.MethodsInternational Physical Activity Questionnaire (IPAQ) questionnaires, filled out by patients enrolled in the prospective PRAEGNANT registry (NCT02338167; n = 1,270) were used to calculate metabolic equivalent task (MET) minutes, which were subsequently categorized into low (n = 138), moderate (n = 995) or high IPAQ categories (n = 137). Cox regression analyses were used to evaluate the impact of IPAQ categories and its interaction with molecular subtypes on PFS and OS.ResultsPatient and tumor characteristics were equally distributed across IPAQ categories. HER2pos, HRpos and TNBC were present in 23.1%, 65.7% and 11.2% of patients, respectively. IPAQ scores did not have an impact on PFS and OS in addition to established prognostic factors, either overall or in particular molecular subtypes (PFS: p = 0.33 and OS: p = 0.08, likelihood ratio test). Exploratory analyses showed higher overall survival rates for high IPAQ categories compared to low/moderate IPAQ categories in luminal B-like breast cancer.ConclusionsSelf-reported physical activity using the IPAQ questionnaire did not significantly affect PFS or OS in patients suffering from metastatic breast cancer. Nevertheless, some hypothesis-generating differences between molecular subtypes could be observed, which may be interesting to evaluate further.

Durable Remission After Targeted Therapy in BRAF V600E–Mutant Metastatic Colorectal Cancer: Case Report

ABSTRACT BRAF mutation leads to constitutive activation of the MAPK pathway and is associated with the immune-activating molecular subtype of colorectal cancer. Targeted therapy for BRAF V600E–mutant metastatic colorectal cancer (CRC) has significantly improved outcomes for these patients when combined with anti–epithelial growth factor receptor (EGFR) therapy. However, most patients ultimately develop disease progression. We report a case of a patient with metastatic-deficient mismatch repair, BRAF V600E–mutated CRC, who achieved a durable complete response to vemurafenib plus cetuximab and chemotherapy despite initial high burden of disease, including peritoneal involvement. Recent clinical trials of combined anti-EGFR/anti–BRAF V600E therapy in BRAF V600E-mutant CRCs have found a few instances of robust response. Further study of combined targeted and chemotherapeutic regimens and the immunogenic properties of BRAF mutation may yield promising results.

TP53 mutation status and consensus molecular subtypes of colorectal cancer in patients from Rwanda

BackgroundMutations in the TP53 tumor suppressor gene are well-established drivers of colorectal cancer (CRC) development. However, data on the prevalence of TP53 variants and their association with consensus molecular subtype (CMS) classification in patients with CRC from Rwanda are currently lacking. This study addressed this knowledge gap by investigating TP53 mutation status concerning CMS classification in a CRC cohort from Rwanda.MethodsFormalin-fixed paraffin-embedded (FFPE) tissue blocks were obtained from 51 patients with CRC at the University Teaching Hospital of Kigali, Rwanda. Exons 4 to 11 and their flanking intron-exon boundaries in the TP53 gene were sequenced using Sanger sequencing to identify potential variants. The recently established immunohistochemistry-based classifier was employed to determine the CMS of each tumor.ResultsSequencing analysis of cancerous tissue DNA revealed TP53 pathogenic variants in 23 of 51 (45.1%) patients from Rwanda. These variants were predominantly missense types (18/23, 78.3%). The most frequent were c.455dup (p.P153Afs*28), c.524G > A (p.R175H), and c.733G > A (p.G245S), each identified in three tumors. Trinucleotide sequence context analysis of the 23 mutations (20 of which were single-base substitutions) revealed a predominance of the [C > N] pattern among single-base substitutions (SBSs) (18/20; 90.0%), with C[C > T]G being the most frequent mutation (5/18, 27.8%). Furthermore, pyrimidine bases (C and T) were preferentially found at the 5ʹ flanking position of the mutated cytosine (13/18; 72.2%). Analysis of CMS subtypes revealed the following distribution: CMS1 (microsatellite instability-immune) (6/51, 11.8%), CMS2 (canonical) (28/51, 54.9%), CMS3 (metabolic) (9/51, 17.6%), and CMS4 (mesenchymal) (8/51, 15.7%). Interestingly, the majority of TP53 variants were in the CMS2 subgroup (14/23; 60.1%).ConclusionOur findings indicate a high frequency of TP53 variants in CRC patients from Rwanda. Importantly, these variants are enriched in the CMS2 subtype. This study, representing the second investigation into molecular alterations in patients with CRC from Rwanda and the first to explore TP53 mutations and CMS classification, provides valuable insights into the molecular landscape of CRC in this understudied population.

Development of a streamlined NGS-based TCGA classification scheme for gastric cancer and its implications for personalized therapy.

The Cancer Genome Atlas (TCGA) has identified four distinct molecular subtypes of gastric cancer (GC) with prognostic significance: Epstein-Barr virus (EBV)-positive, microsatellite instability (MSI)-high, genomically stable (GS), and chromosomal instability (CIN). Unfortunately, the complex analysis required for TCGA classification limits its practical use in clinical settings. Our study sought to devise a next-generation sequencing (NGS)-based method to classify GC more efficiently, serving as a promising biomarker for prognosis and immunotherapy efficacy. This study was a retrospective observation study, and we employed 2 independent GC cohorts. The 3DMed cohort (n=765), comprising data on 733 cancer-related genes along with 4 EBV-encoded genes, was utilized to develop the new NGS classification. Additionally, the secondary Korean cohort (n=55), which includes both genomic data and information on immune checkpoint inhibitor (ICI) treatment, was employed to establish a correlation between NGS subtypes and ICI responsiveness. In the 3DMed cohort, we identified 5.2% EBV, 4.6% MSI, 30.6% GS, and 59.6% CIN subtypes. The MSI subtype exhibited the highest number of mutation events, along with the highest tumor mutational burden (TMB) and strong programmed cell death ligand 1 (PD-L1) expression. CIN tumors showed extensive copy number variations (CNVs) and genomic heterogeneity. The EBV subtype presented recurrent ARID1A and PIK3CA mutations and fewer TP53 mutations. GS tumors exhibited specific mutations in CDH1 and ARID1A. In the Korean cohort, ICIs were most effective in MSI and EBV cases, showing disease control rates of 100%, compared to 62.9% in GS and 12.5% in CIN subtypes. The NGS method successfully maps the mutational landscape of GC, providing a practical TCGA classification surrogate to optimize patient-specific treatment strategies.

Characterization of Molecular Subtypes of Rat Mammary Cancer and Their Association With Environmental Exposures.

Breast cancer is a heterogeneous disease with many subtypes, and the association between these subtypes and exposure to environmental factors such as radiation remains controversial. Although the rat is used widely for research into human breast cancer, the heterogeneity and subtype definitions are unclear. Here, we leveraged an archive of rat mammary cancer samples and gene expression microarray data to classify tumors and examine their association with exposures. Eighty-four mammary cancer and 12 normal mammary tissue samples were obtained from previous experiments in which rats were exposed to different types of radiation, chemical carcinogens, and diets. Tumors were then subjected to immunohistochemical (IHC) analysis of conventional biomarkers, as well as gene expression profiling; they were then classified by three approaches based on IHC results, the PAM50 classifier algorithm, and unsupervised clustering of gene expression profiles. IHC identified four subtypes (luminal A-like, luminal B-like 1, luminal B-like 2, and triple-negative), while PAM50 identified six (luminal A, luminal B, basal-like, HER2-enriched, normal-like, and claudin-low). Unsupervised clustering divided the tumors into three large, statistically significant, groups (named "luminal A", "luminal B", and "non-luminal" clusters). The results of the three approaches were significantly associated with each other. Exposure to radiation and chemical carcinogens during post-pubertal development was significantly associated with an increased risk of developing luminal A tumors, whereas exposure to a high corn-oil diet was associated with a higher likelihood of luminal B tumors. Rat mammary cancer subtypes resemble those in humans and are related to environmental factors.

Exploring the interplay between colorectal cancer subtypes genomic variants and cellular morphology: A deep-learning approach.

Molecular subtypes of colorectal cancer (CRC) significantly influence treatment decisions. While convolutional neural networks (CNNs) have recently been introduced for automated CRC subtype identification using H&E stained histopathological images, the correlation between CRC subtype genomic variants and their corresponding cellular morphology expressed by their imaging phenotypes is yet to be fully explored. The goal of this study was to determine such correlations by incorporating genomic variants in CNN models for CRC subtype classification from H&E images. We utilized the publicly available TCGA-CRC-DX dataset, which comprises whole slide images from 360 CRC-diagnosed patients (260 for training and 100 for testing). This dataset also provides information on CRC subtype classifications and genomic variations. We trained CNN models for CRC subtype classification that account for potential correlation between genomic variations within CRC subtypes and their corresponding cellular morphology patterns. We assessed the interplay between CRC subtypes' genomic variations and cellular morphology patterns by evaluating the CRC subtype classification accuracy of the different models in a stratified 5-fold cross-validation experimental setup using the area under the ROC curve (AUROC) and average precision (AP) as the performance metrics. The CNN models that account for potential correlation between genomic variations within CRC subtypes and their cellular morphology pattern achieved superior accuracy compared to the baseline CNN classification model that does not account for genomic variations when using either single-nucleotide-polymorphism (SNP) molecular features (AUROC: 0.824±0.02 vs. 0.761±0.04, p<0.05, AP: 0.652±0.06 vs. 0.58±0.08) or CpG-Island methylation phenotype (CIMP) molecular features (AUROC: 0.834±0.01 vs. 0.787±0.03, p<0.05, AP: 0.687±0.02 vs. 0.64±0.05). Combining the CNN models account for variations in CIMP and SNP further improved classification accuracy (AUROC: 0.847±0.01 vs. 0.787±0.03, p = 0.01, AP: 0.68±0.02 vs. 0.64±0.05). The improved accuracy of CNN models for CRC subtype classification that account for potential correlation between genomic variations within CRC subtypes and their corresponding cellular morphology as expressed by H&E imaging phenotypes may elucidate the biological cues impacting cancer histopathological imaging phenotypes. Moreover, considering CRC subtypes genomic variations has the potential to improve the accuracy of deep-learning models in discerning cancer subtype from histopathological imaging data.

Prognostic prediction signature and molecular subtype for liver cancer: A CTC/CTM‑related gene prediction model and independent external validation.

Liver cancer is the second leading cause of tumor-related death worldwide, and a serious threat to lives and health. Circulating tumor cells (CTCs) facilitate the progression of various cancers, including liver cancer. The relationship between CTC/circulating tumor microemboli-related genes (CRGs) and the prognosis of liver cancer is unclear. The aim of the present study was to identify CTC/circulating tumour microemboli-related genes (CRGs) in hepatocellular carcinoma and to investigate their clinical significance. Transcriptomic data from The Cancer Genome Atlas (International Cancer Genome Consortium (ICGC) and GSE117623 databases were combined, and differentially expressed CRGs were identified. These were subsequently analyzed via least absolute shrinkage and selection operator and multivariate Cox analyses, and a five-gene risk signature was constructed. The signature was validated in the ICGC and GSE14520 dataset with survival analysis and receiver operating characteristic curve analysis. Immunocyte infiltration, tumor mutation burden (TMB), tumor immune dysfunction and exclusion (TIDE), and the somatic mutation rate were also compared between high- and low-risk groups, based on the median predictive index, to further evaluate the immunotherapeutic value of the model. Molecular subtypes of liver cancer were characterized by the non-negative matrix factorization method and potential therapeutic compounds were evaluated for different subtypes. Nomograms were utilized to predict the prognosis of patients, and the signature was compared with previous literature models. Additionally, the biological function of one of the CRGs, tumor protein p53 inducible protein 3 (TP53I3), in liver cancer was further explored through in vitro experiments. Analysis of the prognostic characteristics of the five CRGs led to the identification of two liver cancer subtypes. Patients in the low-risk group had a longer survival compared with those in the high-risk group, and patients in the latter group were associated with a higher TMB, immunocyte infiltration and somatic mutation rate, and lower TIDE scores. The prognostic profile was validated in the ICGC and GSE14520 datasets and exhibited a good predictive performance. In vitro analysis showed that the knockdown of TP53I3 suppressed liver cancer cell proliferation. In summary, CRGs were used to develop a new prognostic signature to predict the prognosis of patients with liver cancer. This signature may be used to assess the prognosis of patients and may provide new insights for clinical management strategies. In addition, TP53I3 is potentially a therapeutic target for liver cancer.

Prognosis of isolated tumor cells and use of molecular classification in early stage endometrioid endometrial cancer

ObjectiveWe assessed the prognosis and molecular subtypes of early stage endometrioid endometrial cancer with isolated tumor cells within sentinel lymph nodes (SLNs) compared with node negative disease.MethodsPatients diagnosed with stage...

Live-Cell Invasive Phenotyping Uncovers ALK2 as a Therapeutic Target in LKB1-Mutant Lung Cancer.

The acquisition of invasive properties is a prerequisite for tumor progression and metastasis. Molecular subtypes of KRAS-driven lung cancer exhibit distinct modes of invasion that contribute to unique growth properties and therapeutic susceptibilities. Despite this, preclinical strategies designed to exploit growth within the context of invasion are lacking. To address this, we designed an experimental system to screen for targetable signaling pathways linked to active early 3D invasion phenotypes in different molecular subtypes of KRAS-driven lung adenocarcinoma. Combined live-cell imaging of human bronchial epithelial cells in a 3D invasion matrix and transcriptomic profiling identified mutant LKB1-specific upregulation of BMP6. LKB1 loss increased BMP6 signaling, which induced the canonical iron regulatory hormone hepcidin. Intact LKB1 was necessary to maintain BMP6 signaling homeostasis and restrict ALK2/BMP6-fueled growth. Preclinical studies in a Kras/Lkb1-mutant syngeneic mouse model and in a xenograft model showed potent growth suppression by inhibiting the ALK2/BMP6 signaling axis with single-agent inhibitors that are currently in clinical trials. Lastly, BMP6 expression was elevated in tumors of patients with LKB1-mutant early-stage lung cancer. These results are consistent with those of a model in which LKB1 acts as a "brake" to iron-regulated growth and suggest that ALK2 inhibition can be used for patients with LKB1-mutant tumors. Significance: Three-dimensional invasion-linked gene expression analysis reveals a therapeutic vulnerability to inhibition of ALK2/BMP6 signaling in LKB1-mutant lung cancer that can be rapidly translated to the clinic.

Clinical significance of lympho-vascular space invasion in different molecular subtypes of endometrial carcinoma

Objective: To analyze the lympho-vascular space invasion (LVSI) in different molecular subtypes of the cancer genome atlas (TCGA) molecular subtypes of endometrial cancer (EC) and to evaluate the prognostic value of LVSI in EC patients with different molecular subtypes. Methods: A total of 258 patients diagnosed EC undergoing surgery in Peking University People's Hospital from January 2016 to June 2022 were analyzed retrospectively. Among 258 patients, 14 cases were classified as POLE-ultramutated subtype, 43 as high-microsatellite instability (MSI-H) subtype, 155 as copy-number low (CNL) subtype, and 46 as copy-number high (CNH) subtype. Fifty-four patients were positive for LVSI, while 203 tested negative. Results: (1) The incidence of LVSI was found to be highest in the CNH subtype (32.6%,15/46), followed by the MSI-H subtype (27.9%, 12/43), the CNL subtype (16.9%, 26/154), and the POLE-ultramutated subtype (1/14), with statistically significant differences (χ2=7.79, P=0.044). (2) Staging and deep myometrial invasion were higher in the LVSI positive group than those in the LVSI negative group (all P<0.05), except for the POLE-ultramutated subtype. The grade, lymph node metastasis, and the expression of nuclear antigen associated with cell proliferation (Ki-67) were significantly higher in LVSI positive patients than those in LVSI negative EC patients with both MSI-H and CNL subtypes (all P<0.05). In CNL subtypes patients, LVSI was also associated with age, histology subtype,and progesterone receptor (PR; all P<0.05). (3) Of the 257 EC patients, 25 cases recurred during the follow-up period, with a recurrence rate of 9.7% (25/257); among them, the recurrence rate of LVSI positive patients was 22.2% (12/54), which was significantly higher than those with LVSI negative (6.4%, 13/203; χ2=12.15, P<0.001). During the follow-up period, none of the 14 patients with POLE-ultramutated had recurrence; among CNL patients, the recurrence rate was 19.2% (5/26) in LVSI positive patients, which was significantly higher than that in LVSI negative ones (5.5%, 7/128; χ2=3.94, P=0.047); where as no difference were found in both MSI-H [recurrence rates in LVSI positive and negative patients were 2/12 and 9.7% (3/31), respectively] and CNH subtype [recurrence rates between LVSI positive and negative patients were 5/15 and 9.7% (3/31), respectively] EC patients (both P>0.05). After log-rank test, the 3-year recurrence free survival (RFS) rate were significantly lower in LVSI positive patients from CNL subtype and CNH subtype than those in LVSI negative patients (CNL: 80.8% vs 94.5%; CNH: 66.7% vs 90.3%; both P<0.05). (4) Lymph node metastasis (HR=6.93, 95%CI: 1.15-41.65; P=0.034) had a significant effect on the 3-year RFS rate of EC patients with MSI-H subtype. Multivariate analysis revealed that PR expression (HR=0.04, 95%CI: 0.01-0.14;P<0.001) was significantly associated with the 3-year RFS rate of CNL subtype patients. Conclusions: LVSI has the highest positivity rate in CNH subtype, followed by MSI-H subtype, CNL subtype, and the lowest positivity rate in POLE-ultramutated subtype. LVSI is significantly associated with poor prognosis in CNL subtype patients and may affect the prognosis of CNH subtype patients. However, LVSI is not an independent risk factor for recurrence across all four TCGA molecular subtypes.

Molecular Subtype of Small Cell Lung Cancer: Challenge for Transforming into Clinical Practice

Small cell lung cancer (SCLC), one of the histological subtypes of lung cancer, is characterized by high proliferation, early metastasis, susceptibility to drug resistance and recurrence. For several years, SCLC has always been regarded as a homogeneous disease, treated with a unified radiotherapy and chemotherapy strategy. Despite significant early therapeutic effects, drug resistance and recurrence occur quickly, and there is a lack of satisfactory treatment results, which may be due to insufficient understanding of the tumor heterogeneity of SCLC at present. Recently, the concept of SCLC molecular subtype based on the definition of relatively high expression of lineage transcription factors has been proposed in preclinical studies. This article mainly elaborates on the current status and latest findings of SCLC molecular subtype, emphasizing the potential problems that molecular typing may encounter in clinical practice, aiming to promote understanding of the research progress of molecular subtype in SCLC. .

Re: Metastasis and Recurrence Patterns in the Molecular Subtypes of Urothelial Bladder Cancer

Re: Metastasis and Recurrence Patterns in the Molecular Subtypes of Urothelial Bladder Cancer

Molecular Subtypes of Endometrial Cancer and Their Therapeutic Implications: A Review Background

Molecular Subtypes of Endometrial Cancer and Their Therapeutic Implications: A Review Background

Novel molecular subtypes of METex14 non-small cell lung cancer with distinct biological and clinical significance

Not all MET exon 14 skipping (METex14) NSCLC patients benefited from MET inhibitors. We hypothesized an inter-tumoral heterogeneity in METex14 NSCLC. Investigations at genomic and transcriptomic level were conducted in METex14 NSCLC samples from stage I-III and recurrent/metastatic patients as discovery and validation cohort. Four molecular subtypes were discovered. MET-Driven subtype, with the worst prognosis, displayed MET overexpression, enrichment of MET-related pathways, and higher infiltration of fibroblast and regulatory T cells. Immune-Activated subtype having the most idea long-term survival, had higher tertiary lymphoid structures, spatial co-option of PD-L1+ cancer cells, and GZMK+ CD8+ T cell. FGFR- and Bypass-Activated subtypes displayed FGFR2 overexpression and enrichments of multiple oncogenic pathways respectively. In the validation cohort, patients with MET-Driven subtype had better response to MET inhibitors than those with MET overexpression. Thus, molecular subtypes of METex14 NSCLC with distinct biological and clinical significance may indicate more precise therapeutic strategies for METex14 NSCLC patients.

Molecular subtypes of colorectal cancer in the era of precision oncotherapy: Current inspirations and future challenges.

Colorectal cancer (CRC) is among the most hackneyed malignancies. Even patients with identical clinical symptoms and the same TNM stage still exhibit radically different clinical outcomes after receiving equivalent treatment regimens, indicating extensive heterogeneity of CRC. Myriad molecular subtypes of CRC have been exploited for decades, including the most compelling consensus molecular subtype (CMS) classification that has been broadly applied for patient stratification and biomarker-drug combination formulation. Encountering barriers to clinical translation, however, CMS classification fails to fully reflect inter- or intra-tumor heterogeneity of CRC. As a consequence, addressing heterogeneity and precisely managing CRC patients with unique characteristics remain arduous tasks for clinicians. In this review, we systematically summarize molecular subtypes of CRC and further elaborate on their clinical applications, limitations, and future orientations. In recent years, exploration of subtypes through cell lines, animal models, patient-derived xenografts (PDXs), organoids, and clinical trials contributes to refining biological insights and unraveling subtype-specific therapies in CRC. Therapeutic interventions including nanotechnology, clustered regulatory interspaced short palindromic repeat/CRISPR-associated nuclease 9 (CRISPR/Cas9), gut microbiome, and liquid biopsy are powerful tools with the possibility to shift the immunologic landscape and outlook for CRC precise medicine.