Tumor mutation burden and FAT3 mutation influence long-term survival in surgically resected small cell lung cancer.

Background: Small cell lung cancer (SCLC) is highly malignant and has a higher risk of recurrence even in patients who undergo early surgery. However, a subgroup of patients survived for many years. So far, the factors that determine the long-term survivorship remain largely unknown. To determine the genetic characteristics of long-term survival (LTS) after surgery in SCLC, we performed comprehensive comparative genomic profiling and tumor mutation burden (TMB) analysis of resected tumor tissues from patients with LTS and short-term survival (STS) after surgery. Methods: The present study screened 11 patients from 52 patients with SCLC who underwent surgery at Zhejiang Cancer Hospital from April 2008 to December 2017. A total of six LTS patients (≥4 years) with stage IIB or IIIA SCLC and five STS patients (<2 years) with stage IA or IB SCLC were included in the study. The STS patients were used as a control. All the patients underwent resection without neoadjuvant therapy. We assessed the genomic profiles of the resected tumor tissues and calculated the TMB using next-generation sequencing. We then analyzed and compared the molecular characteristics between the LTS and STS groups. Results: Our data indicated that tumor tissues from patients with LTS harbor a high TMB. The median TMB for LTS patients was high (approximately 16.4 mutations/Mb), while that for STS patients was low (approximately 8.5 mutations/Mb). The median TMB of patients with LTS and STS showed a trend of significant difference (P=0.08). Gene alterations characterized the survival differences between the two groups. The FAT3 mutation was only found in the LTS group, and the P value determined by Fisher's exact test was 0.06. Conclusions: A high non-synonymous TMB and the FAT3 mutation could potentially influence LTS after SCLC resection. This study provides valuable information about the molecular differences between LTS and STS patients. Studies with larger sample sizes need to be conducted to confirm our findings in the future.

Dynamic change of cancer genome profiling in metachronous bilateral breast cancer with BRCA pathogenic variant.

A 61-year-old woman with BRCA2 pathogenic variant had been treated for 20 years and showed dynamic changes in the genomic profile of her metachronous bilateral breast cancer and metastases. She underwent right breast conservation surgery at age 42-Genome 1, lung metastasis and left axillary lymph node metastasis at age 51, partial excision under local anesthesia for left breast cancer at age 53-Genome 2, left axillary lymph node dissection was added 6 month later-Genome 3. Then, olaparib was administered, and subsequently, left mastectomy was performed for the recurrence of left breast cancer at age 59-Genome 4. Genomic profile of the tumor was analyzed at four points (Genome 1-3 were analyzed by in house breast cancer panel, and Genome 4 was analyzed by Foundation One CDx). Two interesting findings emerged from these analyses. First, the genomic profile revealed that the left axillary lymph node metastasis, considered histologically from right breast cancer, was a metastasis from the left breast cancer. The second finding is that as the disease progressed, mutation profile became more diverse. The profile of the left breast cancer removed after olaparib and other treatments showed reversion mutation of BRCA2 and was diagnosed as tumor mutation burden high. Subsequent response to pembrolizumab was favorable.

[Whole Exome Sequencing Reveals Gene Mutation Characteristics of Primary Central Nervous System Lymphoma].

OBJECTIVE: To investigate gene mutation characteristics of primary central nervous system lymphoma (PCNSL) through whole exome sequencing (WES) to 18 patients with PCNSL. METHODS: Tumor tissues from 18 patients with diffuse large B-cell lymphoma who were diagnosed with PCNSL in Department of Hematology, Lanzhou University Second Hospital from September 2018 to December 2020 and had normal immune function, no history of HIV or immunosuppressant therapy were collected. High-throughput-based WES was performed on the tumor tissues, with an average sequencing depth of >100×. After data processing and bioinformatics analysis of sequencing results, the mutation maps and mutation characteristics of 18 PCNSL patients were obtained. RESULTS: Obvious somatic mutations were detected in all 18 patients. The median number of somatic mutations was 321. Missense mutations were most prominent (accounting for about 90%), and the mutation type was dominated by C>T (50.2%), reflecting the age-related mutation pattern. Among the top 15 frequently mutated genes, PSD3, DUSP5, MAGEB16, TELO2, FMO2, TRMT13, AOC1, PIGZ, SVEP1, IP6K3, and TIAM1 were the driver genes. The enrichment results of driver gene pathways showed that RTK-RAS, Wnt, NOTCH, Hippo and Cell-Cycle pathways were significantly enriched. The tumor mutation burden was between 3.558 48/Mb and 8.780 89/Mb, and the average was 4.953 32/Mb, which was significantly higher than other cancer research cohorts in the TCGA database. CONCLUSIONS: PCNSL occurs somatic missense mutations frequently, mainly point mutations, and the mutation type is mainly C>T. The driver genes are mainly involved in RTK-RAS, Wnt, NOTCH and Hippo pathways, indicating that the above pathways may be related to the pathogenesis of PCNSL. PCNSL has a significantly high tumor mutation burden, which may explain the efficacy of PD-1 inhibitors in PCNSL.

Developing a prognostic model for skin melanoma based on the persistent tumor mutation burden and determining IL17REL as a therapeutic target.

BACKGROUND: One popular and well-established marker for the immune checkpoint blockade (ICB) response is tumor mutation burden (TMB). Persistent TMB (pTMB), a subset of TMB, provides a better indicator to predict patient ICB therapy outcomes, as shown by some studies. Immune checkpoint drugs have significantly changed how melanoma is treated in recent years. METHODS: In this study, we integrated the TCGA-SKCM database and data of pTMB of TCGA from the paper that first mentioned pTMB and analyzed mutational and Immune characteristics associated with pTMB level in SKCM. Next, the predictive DEGs were identified the subgroups of pTMB by Cox regression and LASSO analyses to construct a pTMB-related signature. Finally, the expression and Biological functions of signature genes was detected, and further validated in vitro assay. RESULTS: In the current research, we explored the mutational and immunological features related to the level of TMB in cutaneous melanoma (CM). The high-pTMB subgroup exhibited an increasing incidence of gene changes and higher levels of immune cell infiltration. Subsequently, we established a pTMB-related signature based on the predictive DEGs and found the biological features and immune-associated variables between two distinct risk groups. Lastly, the results of the clinical sample validation demonstrated that the expression of IL17REL was down-regulated in the collected samples of individuals with CM. The in vitro assay results indicated that IL17REL effectively suppressed the proliferation, clonality, and migration of CM cells. CONCLUSION: In conclusion, we have developed a prediction model associated with TMB and subsequently validated the potential influence of IL17REL on Overall Survival (OS) in patients diagnosed with melanoma.

Concomitant genomic features stratify prognosis to patients with advanced EGFR mutant lung cancer.

This study aimed to explore the clinical significance of genomics features including tumor mutation burden (TMB) and copy number alteration (CNA) for advanced EGFR mutant lung cancer. We retrospectively identified 1378 patients with advanced EGFR mutant lung cancer and next-generation sequencing tests from three cohorts. Multiple co-occurring genomics alternations occurred in a large proportion (97%) of patients with advanced EGFR mutant lung cancers. Both TMB and CNA were predictive biomarkers for these patients. A joint analysis of TMB and CNA found that patients with high TMB and high CNA showed worse responses to EGFR-TKIs and predicted worse outcomes. TMBhighCNAhigh, as a high-risk genomic feature, showed predictive ability in most of the subgroups based on clinical characteristics. These patients had larger numbers of metastatic sites, and higher rates of EGFR copy number amplification, TP53 mutations, and cell-cycle gene alterations, which showed more potential survival gain from combination treatment. Furthermore, a nomogram based on genomic features and clinical features was developed to distinguish prognosis. Genomic features could stratify prognosis and guide clinical treatment for patients with advanced EGFR mutant lung cancer.

Comprehensive bioinformatics analysis of human cytomegalovirus pathway genes in pan-cancer.

BACKGROUND: Human cytomegalovirus (HCMV) is a herpesvirus that can infect various cell types and modulate host gene expression and immune response. It has been associated with the pathogenesis of various cancers, but its molecular mechanisms remain elusive. METHODS: We comprehensively analyzed the expression of HCMV pathway genes across 26 cancer types using the Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) databases. We also used bioinformatics tools to study immune invasion and tumor microenvironment in pan-cancer. Cox regression and machine learning were used to analyze prognostic genes and their relationship with drug sensitivity. RESULTS: We found that HCMV pathway genes are widely expressed in various cancers. Immune infiltration and the tumor microenvironment revealed that HCMV is involved in complex immune processes. We obtained prognostic genes for 25 cancers and significantly found 23 key genes in the HCMV pathway, which are significantly enriched in cellular chemotaxis and synaptic function and may be involved in disease progression. Notably, CaM family genes were up-regulated and AC family genes were down-regulated in most tumors. These hub genes correlate with sensitivity or resistance to various drugs, suggesting their potential as therapeutic targets. CONCLUSIONS: Our study has revealed the role of the HCMV pathway in various cancers and provided insights into its molecular mechanism and therapeutic significance. It is worth noting that the key genes of the HCMV pathway may open up new doors for cancer prevention and treatment.

Advanced Cholangiocarcinoma With High Tumor Mutation Burden Achieving Complete Response to Immune Check Point Inhibitor.

BACKGROUND/AIM: Genomic examination of tumor tissue has been clinically accepted, and the identification of actionable mutations for molecular-targeted therapy may provide substantial survival benefit for patients with advanced malignancies. CASE REPORT: A female patient in her 60s showed a stenosis of the afferent loop of the small intestine because of circumferential metastatic tumor 14 months after curative surgery for hilar cholangiocarcinoma. Chemotherapy with gemcitabine plus cisplatin was administered for 18 months. An oncopanel examination was performed during chemotherapy, and a high tumor mutation burden was revealed. At 38 months after surgery, a new recurrent tumor, 2.7 cm in size, was observed in the abdominal wall, which was histologically proven to be metastatic adenocarcinoma. Atezolizumab was administered. After three cycles of treatment, treatment was switched to pembrolizumab because of its acceptance by healthcare insurance. The recurrent tumors in the abdominal wall and small intestine disappeared 6 months after the administration of immune checkpoint inhibitor, and the patient has continued pembrolizumab, surviving for 76 months after surgery without any clinical evidence of tumor. CONCLUSION: Immune checkpoint blockade successfully prolonged the survival of a patient with advanced hilar cholangiocarcinoma with high tumor mutation burden, although the optimal number of mutations for such a successful response needs to be clarified.

Colorectal cancer subtyping and immune landscape analysis based on natural killer cell-related genes.

BACKGROUND AND STUDY AIMS: The prognosis of colorectal cancer (CRC) is related to natural killer (NK) cells, but the molecular subtype features of CRC based on NK cells are still unknown. This study aimed to identify NK cell-related molecular subtypes of CRC and analyze the survival status and immune landscape of patients with different subtypes. PATIENTS/MATERIAL AND METHODS: mRNA expression data, single nucleotide variant (SNV) data, and clinical information of CRC patients were obtained from The Cancer Genome Atlas. Differentially expressed genes (DEGs) were obtained through differential analysis, and the intersection was taken with NK cell-associated genes to obtain 103 NK cell-associated CRC DEGs (NCDEGs). Based on NCDEGs, CRC samples were divided into three clusters through unsupervised clustering analysis. Survival analysis, immune analysis, Gene Set Enrichment Analysis (GSEA), and tumor mutation burden (TMB) analysis were performed. Finally, NCDEG-related small-molecule drugs were screened using the CMap database. RESULTS: Survival analysis revealed that cluster2 had a lower survival rate than cluster1 and cluster3 (p < 0.05). Immune infiltration analysis found that the immune infiltration levels and immune checkpoint expression levels of cluster1_3 were substantially higher than those of cluster2, and the tumor purity was the opposite (p < 0.05). GSEA presented that cluster1_3 was significantly enriched in the chemokine signaling pathway, ECM receptor interaction, and antigen processing and presentation pathways (p < 0.05). The TMB of cluster1_3 was significantly higher than that of cluster2 (p < 0.05). Genes with the highest mutation rate in CRC were APC, TP53, TTN, and KRAS. Drug prediction results showed that small-molecule drugs that reverse the upregulation of NCDEGs, deoxycholic acid, dipivefrine, phenformin, and other drugs may improve the prognosis of CRC. CONCLUSION: NK cell-associated CRC subtypes can be used to evaluate the tumor characteristics of CRC patients and provide an important reference for CRC patients.

Advanced gallbladder cancer with high tumor mutation burden: a case report and literature review.

Background: Gallbladder cancer (GBC) is a common malignant tumor of the biliary system. It is characterised by insidious onset, rapid progression and poor prognosis. Symptoms often indicate advanced or late-stage disease, with a 5-year survival rate of only 5-15%. Case Description: We present a case study of a patient with GBC who had a tumor mutation burden (TMB) of 32.5/MB (≥10 muts/MB). The patient received mFOLFIRINOX as first-line chemotherapy, which demonstrated significant efficacy. After stabilizing the disease, a sequential chemotherapy regimen was chosen. This regimen combined the immune checkpoint inhibitor (ICI) toripalimab (JS001), a humanised IgG4 monoclonal antibody targeting programmed cell death protein 1 (PD-1), with S-1 therapy, an oral fluoropyrimidine derivative. However, this treatment did not provide any significant clinical benefit for the patient. Therefore, we hypothesise that combining immunotherapy with chemotherapy may be more effective as a first line treatment for high-TMB advanced GBC. This hypothesis needs to be validated in large-scale clinical studies. Conclusions: In summary, mFOLFIRINOX is a safe and effective first-line chemotherapy regimen for advanced GBC. The timing of combining immunotherapy with chemotherapy requires careful consideration. Further clinical trials involving immunotherapy in advanced GBC are necessary to identify biomarkers that can guide clinical decisions.

Survival in metastatic microsatellite-stable colorectal cancer correlated with tumor mutation burden and mutations identified by next-generation sequencing.

Background: Next-generation sequencing (NGS) identifies mutations and molecular abnormalities within tumors, including tumor mutation burden (TMB). If a solid tumor has high TMB, immune checkpoint inhibitors (ICIs) are approved as an option for treatment. Studies have been inconclusive regarding how effective ICI are in treating patients with colorectal cancer (CRC), and it is unclear if high TMB is a good prognostic marker for CRC. We collected data from NGS of CRC and correlated survival to both TMB and mutations of interest, as well as investigated the efficacy of ICI. Methods: This was a retrospective cohort analysis at a single institution, collecting NGS data from January 2018 to December 2020 in patients with CRC who were microsatellite-stable (MSS), n=161. Demographics, clinical data, and results from NGS were collected, and a survival analysis looking at TMB and selected mutations of interest was performed. Patients who were treated with ICI were assessed in a descriptive subset analysis. Results: Patients with CRC who were MSS and had high TMB trended towards worse survival [hazard ratio (HR) =1.38] though the result was not significant (P=0.28). Survival was significantly worse in patients with a KRAS mutation (HR =1.71, P=0.04) and/or a CDKN2A mutation (HR =4.45, P<0.001). In this study population, 12 patients with high TMB had treatment with ICI, with nine of these patients having shorter progression-free survival (PFS) between 0.7 and 4.1 months, and three patients having longer PFS of 26.3, 24.7, and 13.2 months. Conclusions: High TMB in MSS CRC did not show statistical difference in outcome. Mutations in KRAS and/or CDKN2A correlated with worse prognosis. Some patients with MSS CRC and high TMB responded to ICI, though there is a need to identify a better biomarker to predict which patients will have a good response to ICI therapy.

Predictive value of PD-L1 and TMB for short-term efficacy prognosis in non-small cell lung cancer and construction of prediction models.

Objective: To investigate the correlation between programmed death ligand 1(PD-L1), tumor mutation burden (TMB) and the short-term efficacy and clinical characteristics of anti-PD-1 immune checkpoint inhibitor combination chemotherapy in NSCLC patients. The efficacy of the prediction model was evaluated. Methods: A total of 220 NSCLC patients receiving first-line treatment with anti-PD-1 immune checkpoint inhibitor combined with chemotherapy were retrospectively collected. The primary endpoint was short-term efficacy ORR. The correlation between short-term efficacy, PD-L1, TMB, and clinical characteristics using χ2 test or t-test was evaluated. Screen the independent prognostic factors using univariate and multivariate logistic regression analyses, and construct a nomogram prediction model using the "rms" package in R software. Using receiver operating characteristic (ROC) curve analysis to evaluate the independent Prognostic factors and the prediction model. Using decision curve analysis (DCA) to verify the superiority of the prediction model. Results: The mean values of PD-L1, TMB, neutrophils, lymphocytes, neutrophil-to-lymphocyte ratio, and albumin were the highest in the ORR group, PD-L1 expression and TMB correlated with epidermal growth factor receptor expression. Multivariate analyses showed that PD-L1, TMB, and neutrophil were independent prognostic factors for ORR. The area under the ROC curve (AUC) values of the ROC constructed based on these three indicators were 0.7104, 0.7139, and 0.7131, respectively. The AUC value under the ROC of the nomogram model was 0.813. The DCA of the model showed that all three indicators used together to build the prediction model of the net return were higher than those of the single indicator prediction model. Conclusion: PD-L1, TMB, and neutrophils are independent prognostic factors for short-term efficacy. The nomogram prediction model constructed using these three indicators can further improve predictive efficacy of ICIs in patients with NSCLC.

Microsatellite Instability, Mismatch Repair, and Tumor Mutation Burden in Lung Cancer.

Since US Food and Drug Administration approval of programmed death ligand 1 (PD-L1) as the first companion diagnostic for immune checkpoint inhibitors (ICIs) in non-small cell lung cancer, many patients have experienced increased overall survival. To improve selection of ICI responders versus nonresponders, microsatellite instability/mismatch repair deficiency (MSI/MMR) and tumor mutation burden (TMB) came into play. Clinical data show PD-L1, MSI/MMR, and TMB are independent predictive immunotherapy biomarkers. Harmonization of testing methodologies, optimization of assay design, and results analysis are ongoing. Future algorithms to determine immunotherapy eligibility might involve complementary use of current and novel biomarkers. Artificial intelligence could facilitate algorithm implementation to convert complex genetic data into recommendations for specific ICIs.

Synchronous Triple Malignancy of Esophagus, Pancreas, and Pyriform Sinus: A Prima Facie Report.

The occurrence of triple synchronous primary malignant neoplasms is very rare. With improved cancer detection rates, widespread screening techniques and their availability, and improved general awareness, there has been a rise in the detection rate of patients with multiple primaries. Most of these cases consist of dual synchronous malignancies. However, triple synchronous malignancies have been reported and are extremely rare in literature. In such cases, the etiology is unknown most of the time, and management of such a situation remains challenging. We report such a case in a 71-year-old male with no genetic predisposition or family history of malignancy, presenting with three primary malignancies of the buccal mucosa, esophagus, and pancreas. Investigations revealed three histologically separate tumors in the buccal mucosa, esophagus, and pancreas. The patient was treated initially with a first-line combination of chemotherapy and later with a 2nd-line palliative chemotherapy. The prognosis of such patients is poor. Our patient is still on 2nd-line palliative chemotherapy without any major complications.

TM-Score predicts immunotherapy efficacy and improves the performance of the machine learning prognostic model in gastric cancer.

Immunotherapy is becoming increasingly important, but the overall response rate is relatively low in the treatment of gastric cancer (GC). The application of tumor mutational burden (TMB) in predicting immunotherapy efficacy in GC patients is limited and controversial, emphasizing the importance of optimizing TMB-based patient selection. By combining TMB and major histocompatibility complex (MHC) related hub genes, we established a novel TM-Score. This score showed superior performance for immunotherapeutic selection (AUC = 0.808) compared to TMB, MSI status, and EBV status. Additionally, it predicted the prognosis of GC patients. Subsequently, a machine learning model adjusted by the TM-Score further improved the accuracy of survival prediction (AUC > 0.8). Meanwhile, we found that GC patients with low TM-Score had a higher mutation frequency, higher expression of HLA genes and immune checkpoint genes, and higher infiltration of CD8+ T cells, CD4+ helper T cells, and M1 macrophages. This suggests that TM-Score is significantly associated with tumor immunogenicity and tumor immune environment. Notably, based on the RNA-seq and scRNA-seq, it was found that AKAP5, a key component gene of TM-Score, is involved in anti-tumor immunity by promoting the infiltration of CD4+ T cells, NK cells, and myeloid cells. Additionally, siAKAP5 significantly reduced MHC-II mRNA expression in the GC cell line. In addition, our immunohistochemistry assays confirmed a positive correlation between AKAP5 and human leukocyte antigen (HLA) expression. Furthermore, AKAP5 levels were higher in patients with longer survival and those who responded to immunotherapy in GC, indicating its potential value in predicting prognosis and immunotherapy outcomes. In conclusion, TM-Score, as an optimization of TMB, is a more precise biomarker for predicting the immunotherapy efficacy of the GC population. Additionally, AKAP5 shows promise as a therapeutic target for GC.

Automated Quantitative CD8+ Tumor-Infiltrating Lymphocytes and Tumor Mutation Burden as Independent Biomarkers in Melanoma Patients Receiving Front-Line Anti-PD-1 Immunotherapy.

BACKGROUND: CD8+ tumor-infiltrating lymphocyte (TIL) predicts response to anti-PD-(L)1 therapy. However, there remains no standardized method to assess CD8+ TIL in melanoma, and developing a specific, cost-effective, reproducible, and clinically actionable biomarker to anti-PD-(L)1 remains elusive. We report on the development of automatic CD8+ TIL density quantification via whole slide image (WSI) analysis in advanced melanoma patients treated with front-line anti-PD-1 blockade, and correlation immunotherapy response. METHODS: Seventy-eight patients treated with PD-1 inhibitors in the front-line setting between January 2015 and May 2023 at the University of Pittsburgh Cancer Institute were included. CD8+ TIL density was quantified using an image analysis algorithm on digitized WSI. Targeted next-generation sequencing (NGS) was performed to determine tumor mutation burden (TMB) in a subset of 62 patients. ROC curves were used to determine biomarker cutoffs and response to therapy. Correlation between CD8+ TIL density and TMB cutoffs and response to therapy was studied. RESULTS: Higher CD8+ TIL density was significantly associated with improved response to front-line anti-PD-1 across all time points measured. CD8+ TIL density ≥222.9 cells/mm2 reliably segregated responders and non-responders to front-line anti-PD-1 therapy regardless of when response was measured. In a multivariate analysis, patients with CD8+ TIL density exceeding cutoff had significantly improved PFS with a trend toward improved OS. Similarly, increasing TMB was associated with improved response to anti-PD-1, and a cutoff of 14.70 Mut/Mb was associated with improved odds of response. The correlation between TMB and CD8+ TIL density was low, suggesting that each represented independent predictive biomarkers of response. CONCLUSIONS: An automatic digital analysis algorithm provides a standardized method to quantify CD8+ TIL density, which predicts response to front-line anti-PD-1 therapy. CD8+ TIL density and TMB are independent predictors of response to anti-PD-1 blockade.

TMBstable: a variant caller controls performance variation across heterogeneous sequencing samples.

In cancer genomics, variant calling has advanced, but traditional mean accuracy evaluations are inadequate for biomarkers like tumor mutation burden, which vary significantly across samples, affecting immunotherapy patient selection and threshold settings. In this study, we introduce TMBstable, an innovative method that dynamically selects optimal variant calling strategies for specific genomic regions using a meta-learning framework, distinguishing it from traditional callers with uniform sample-wide strategies. The process begins with segmenting the sample into windows and extracting meta-features for clustering, followed by using a pre-trained meta-model to select suitable algorithms for each cluster, thereby addressing strategy-sample mismatches, reducing performance fluctuations and ensuring consistent performance across various samples. We evaluated TMBstable using both simulated and real non-small cell lung cancer and nasopharyngeal carcinoma samples, comparing it with advanced callers. The assessment, focusing on stability measures, such as the variance and coefficient of variation in false positive rate, false negative rate, precision and recall, involved 300 simulated and 106 real tumor samples. Benchmark results showed TMBstable's superior stability with the lowest variance and coefficient of variation across performance metrics, highlighting its effectiveness in analyzing the counting-based biomarker. The TMBstable algorithm can be accessed at https://github.com/hello-json/TMBstable for academic usage only.

Molecular characteristics and multivariate survival analysis of 43 patients with locally advanced or metastatic esophageal squamous cell carcinoma.

Background: Esophageal cancer (EC) is an aggressive malignant tumor with poor prognosis and high incidence. It is the sixth leading cause of cancer-related death in the world, and the 5-year overall survival (OS) rate is only 12-20%. The rapid development of next-generation sequencing (NGS) has provided powerful help for the treatment and management of EC patients. Methods: Tumor tissue and blood samples of 43 Chinese patients with nonsurgical esophageal squamous cell carcinoma (ESCC) were sequenced using a 425 gene-panel. Genomic profiling was explored and and the Cox proportional hazards model was used to analyze the correlations between gene or signaling pathway alterations and prognosis. Results: In this study, the most common mutated genes were TP53 (90.5%), CCND1 (45.2%), FGF19 (38.1%), NOTCH1 (26.2%), PI3KCA (21.4%) and CDKN2A (19%). Among these mutations, PI3KCA and NOTCH1 showed mutual exclusion to some extent. In the univariate model, mutations in NOTCH1, CBLB and TSC2 genes and tumor mutation burden (TMB) ≥7 were independent biomarkers of OS. NOTCH1 (P=0.007, HR =2.87), CBLB (P=0.011, HR =4.68) and TSC2 (P=0.024, HR =3.7) were significantly associated with poorer OS, and patients with TMB ≥7 had longer OS (P=0.151, HR =0.31). In addition, patients who carried alteration in NOTCH signaling pathway had reduced OS (P=0.014, HR =2.54). Conclusions: NOTCH1, CBLB and TSC2 alterations were found to be potential indicators of poor prognosis in patients with ESCC. TMB was also positively correlated with the OS of ESCC patients, providing valuable insights for their treatment strategies.

Tumor Mutation Burden as a Cornerstone in Precision Oncology Landscapes: Effect of Panel Size and Uncertainty in Cutoffs.

Tumor mutation burden (TMB) has profound implications for personalized cancer therapy, particularly immunotherapy. However, the size of the panel and the cutoff values for an accurate determination of TMB are still controversial. In this study, a pan-cancer analysis was performed on 22 cancer types from The Cancer Genome Atlas. The efficiency of gene panels of different sizes and the effect of cutoff values in accurate TMB determination was assessed on a large cohort using Whole Exome Sequencing data (n = 9929 patients) as the gold standard. Gene panels of four different sizes (i.e., 0.44-2.54 Mb) were selected for comparative analyses. The heterogeneity of TMB within and between cancer types is observed to be very high, and it becomes possible to obtain the exact TMB value as the size of the panel increases. In panels with limited size, it is particularly difficult to recognize patients with low TMB. In addition, the use of a general TMB cutoff can be quite misleading. The optimal cutoff value varies between 5 and 20, depending on the TMB distribution of the different tumor types. The use of comprehensive gene panels and the optimization of TMB cutoff values for different cancer types can make TMB a robust biomarker in precision oncology. Moreover, optimization of TMB can help accelerate translational medicine research, and by extension, delivery of personalized cancer care in the future.

Comprehensive genomic profiling of pulmonary spindle cell carcinoma using tissue and plasma samples: insights from a real-world cohort analysis.

Pulmonary spindle cell carcinoma (PSCC) is a rare and aggressive non-small cell lung cancer (NSCLC) subtype with a dismal prognosis. The molecular characteristics of PSCC are largely unknown due to its rarity, which limits the diagnosis and treatment of this historically poorly characterized malignancy. We present comprehensive genomic profiling results of baseline tumor samples from 22 patients histologically diagnosed with PSCC, representing the largest cohort to date. Somatic genetic variant detection was compared between paired plasma samples and primary tumors from 13 patients within our cohort. The associations among genomic features, treatment, and prognosis were also analyzed in representative patient cases. TP53 (54.5%), TERT (36.4%), CDKN2A (27.3%), and MET (22.7%) were most frequently mutated. Notably, 81.8% of patients had actionable targets in their baseline tumors, including MET (22.7%), ERBB2 (13.6%), EGFR (9.1%), KRAS (9.1%), ALK (9.1%), and ROS1 (4.5%). The median tumor mutation burden (TMB) for PSCC tumors was 5.5 mutations per megabase (muts/Mb). TMB-high tumors (>10 muts/Mb) exhibited a significantly higher mutation frequency in genes such as KRAS, ARID2, FOXL2, and LRP1B, as well as within the DNA mismatch repair pathway. The detection rates for single nucleotide variants and structural variants were comparable between matched tumor and plasma samples, with 48.6% of genetic variants being mutually identified in both sample types. Additionally, a patient with a high mutation load and positive PD-L1 expression demonstrated a 7-month survival benefit from chemoimmunotherapy. Furthermore, a patient with an ALK-rearranged tumor achieved a remarkable 3-year progression-free survival following crizotinib treatment. Overall, our findings deepen the understanding of the complex genomic landscape of PSCC, revealing actionable targets amenable to tailored treatment of this poorly characterized malignancy.

Ferroptosis biomarkers predict tumor mutation burden's impact on prognosis in HER2-positive breast cancer.

BACKGROUND: Ferroptosis has recently been associated with multiple degenerative diseases. Ferroptosis induction in cancer cells is a feasible method for treating neoplastic diseases. However, the association of iron proliferation-related genes with prognosis in HER2+ breast cancer (BC) patients is unclear. AIM: To identify and evaluate fresh ferroptosis-related biomarkers for HER2+ BC. METHODS: First, we obtained the mRNA expression profiles and clinical information of HER2+ BC patients from the TCGA and METABRIC public databases. A four-gene prediction model comprising PROM2, SLC7A11, FANCD2, and FH was subsequently developed in the TCGA cohort and confirmed in the METABRIC cohort. Patients were stratified into high-risk and low-risk groups based on their median risk score, an independent predictor of overall survival (OS). Based on these findings, immune infiltration, mutations, and medication sensitivity were analyzed in various risk groupings. Additionally, we assessed patient prognosis by combining the tumor mutation burden (TMB) with risk score. Finally, we evaluated the expression of critical genes by analyzing single-cell RNA sequencing (scRNA-seq) data from malignant vs normal epithelial cells. RESULTS: We found that the higher the risk score was, the worse the prognosis was (P < 0.05). We also found that the immune cell infiltration, mutation, and drug sensitivity were different between the different risk groups. The high-risk subgroup was associated with lower immune scores and high TMB. Moreover, we found that the combination of the TMB and risk score could stratify patients into three groups with distinct prognoses. HRisk-HTMB patients had the worst prognosis, whereas LRisk-LTMB patients had the best prognosis (P < 0.0001). Analysis of the scRNA-seq data showed that PROM2, SLC7A11, and FANCD2 were significantly differentially expressed, whereas FH was not, suggesting that these genes are expressed mainly in cancer epithelial cells (P < 0.01). CONCLUSION: Our model helps guide the prognosis of HER2+ breast cancer patients, and its combination with the TMB can aid in more accurate assessment of patient prognosis and provide new ideas for further diagnosis and treatment.