Tumor Mutation Research Articles

Atypical Multifocal Granular Cell Tumor with FLT3 Y842C Somatic Mutation: A case report and a review of the literature.

Granular cell tumors (GCT) are predominantly benign neoplasms composed by cells with abundant eosinophilic granular cytoplasm. Although the majority of GCTs exhibit a benign clinical course, a minority display cytological atypia and may exhibit aggressive, cancer-like behavior. Definitive evidence of malignancy in GCTs is reliably established only through the presence of metastasis. Addi- tionally, a subset of GCTs demonstrates a high rate of recurrence, underscoring the need for better prog- nostic markers. Therefore, it is crucial to identify molecular markers associated with aggressive behavior in GCTs. Molecular analysis may be particularly beneficial in cases exhibiting cytological atypia to in- form clinical outcome prognostication and guide therapeutic strategies. In this case report, a 45-year-old female with multiple gastrointestinal GCTs is pre- sented. The patient did not have any genetic syndromes commonly associated with GCT, such as neu- rofibromatosis type 1, Noonan syndrome or LEOPARD syndrome. The tumors not only demonstrated nuclear atypia, but also harbored a unique FLT3 Y842C somatic alteration identified by next-genera- tion sequencing. The patient remains asymptomatic and under endoscopic surveillance two years after diagnosis and complete resection of the neoplasms. We presented an exceedingly rare case of multifocal atypical GCT in an adult without any previously known genetic syndrome. A tumoral FLT3 Y842C point mutation not previously reported in GCT was discovered. Although the precise significance of this finding is uncertain, FLT3 Y842C has been cataloged as likely pathogenic in ClinVar. This report underscores the potential predictive utility of next-generation sequencing in the characterization and management of rare neoplasms.

Immune-related glycosylation genes based classification predicts prognosis and therapy options of osteosarcoma

Osteosarcoma is the most common primary bone malignancy, with a very poor prognosis. Aberrant glycosylation is close involvement in osteosarcoma. Accordingly, this study aimed at investigating the role of glycosylation genes in the prognosis and therapy options of osteosarcoma. The microenvironment of osteosarcoma was assessed using estimate algorithm. A total of 20 immune-related glycosylation genes (IRGGs) was identified using Pearson correlation analysis. Accordingly, osteosarcoma patients were divided into C1 and C2 type using consensus clustering. Multiple algorithms (Xcell, MCP-counter, ssGSEA, epic, quantiseq), cancer immune cycle analysis, and GSVA were applied to estimate the immune, molecule and metabolism characteristics of osteosarcoma, indicating that C1 type was featured with high immune infiltration, high glycosylation, enriched MEK signaling, and good prognosis, while C2 type was characterized by more metastasis, enriched immunotherapy-positive gene signatures, high tumor mutation burden, and poor prognosis. Results from TIDE algorithm and immunotherapy datasets suggested the C2 type’s preference of immune checkpoint inhibitors (ICIs), while data of GDSC, CMap analysis and cell experiments indicated that C1 type was sensitivity to MEK inhibitor PD0325901. In addition, univariate Cox and Lasso analysis was combined to establish an IRGGs’ risk score containing 6 genes (B3GNT8, FUT7, GAL3ST4, GALNT14, HS3ST2, and MFNG). The data of DCA and ROC indicated its well prediction of prognosis in osteosarcoma. Finally, cellular location analysis showed that the 6 genes not only distributed in tumor cells but also in immune cells. In summary, the classification and risk score based on IRGGs effectively predicted the prognosis and therapy options of osteosarcoma. Further studies on IRGGs may contribute to the understanding of cancer immunity in osteosarcoma.

Predictive value of ZFHX4 mutation for the efficacy of immune checkpoint inhibitors in non-small cell lung cancer and melanoma.

Studies have shown that the Zinc finger homeobox 4 (ZFHX4) might be a factor in the prognosis of malignancies. However, little is known about the association between the ZFHX4 mutation and the effectiveness of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC) and melanoma. Three public ICIs-treated NSCLC cohorts were divided into discovery cohort (n=75) and validation cohort (n=62), which were used to evaluate the relationship between ZFHX4 mutation and ICIs effectiveness in NSCLC. Seven ICIs-treated melanoma cohorts (n = 418) were used to analyze the relationship between ZFHX4 mutation and immunotherapy efficacy in melanoma. NSCLC and skin cutaneous melanoma (SKCM) cohorts from The Cancer Genome Atlas (TCGA) were used to investigate underlying mechanism. Patients with ZFHX4 mutant-type (ZFHX4-Mut) showed a superior objective response rate (ORR) (P < 0.01) and longer progression-free survival (PFS) (P < 0.05) than patients with ZFHX4 wild-type (ZFHX4-WT) in NSCLC cohorts. In the melanoma cohorts, patients carrying ZFHX4-Mut had a higher ORR (P = 0.042) and longer overall survival (OS) (P = 0.011). Besides, patients with NSCLC and melanoma harboring ZFHX4-Mut had a higher tumor mutation burden (TMB) (P<0.001) and tumor neoantigen burden (TNB) (P<0.001) than those harboring ZFHX4-WT. ZFHX4 mutation was associated with higher levels of plasma B cells, activated CD4+ memory T cells, and CD8+ T cells. Seven DNA damage repair pathways were significantly enriched in the ZFHX4-Mut group. ZFHX4 mutation could serve as a predicter for the efficacy of ICIs therapy in NSCLC and melanoma.

DAXX is associated with early recurrence of pancreatic neuroendocrine tumors after R0 resection

IntroductionATRX, DAXX, MEN1, and PTEN mutations are proposed drivers of pancreatic neuroendocrine tumor tumorigenesis and independent prognostic factors for metastasis and mortality. However, their implications after R0 resection remain debated. Thus, we sought to identify genomic signatures of pancreatic neuroendocrine tumor disease-specific mortality and recurrence after surgery for curative intent. MethodsPancreatic neuroendocrine tumor patients who underwent whole exome sequencing with available survival data were identified using cBioPortal. Clinicopathologic variables, genomics, and outcomes were analyzed. ResultsSeventy patients who underwent R0 resection were identified. Forty-five of 70 patients were disease free at last follow-up, whereas 25 of 70 patients had disease-specific mortality or recurrent disease and therefore were categorized as part of the recurrent cohort. There were no significant differences in age (P = .245), sex (P = .201), or median follow-up (38.9 vs 33.7 months, P = .122) between groups. Clinicopathologically, the recurrent cohort had significantly greater tumor size (median 5.0 cm vs 3.2 cm, P = .012) and were more likely to have vascular invasion (88% vs 40%, P = .000), positive lymph nodes (68.0% vs 35.6%, P = .013), and metastatic disease (44% vs 4.4%, P < .000). For both cohorts, most tumors were well or moderately differentiated. Tumor mutation burden was greater in the recurrent cohort (median 0.77 vs 0.43 mutations/Mb, P = .004). DAXX mutations were more frequent in the recurrent cohort (36% vs 11%, P = .026) and in those with vascular invasion (51% vs 92%, P = .010). ConclusionOur analysis demonstrated the prognostic significance of DAXX mutations after curative-intent surgery. Future studies investigating DAXX mutations as a biomarker for aggressive features to guide treatment are warranted.

Prognostic value of a lactate metabolism gene signature in lung adenocarcinoma and its associations with immune checkpoint blockade therapy response.

Lung adenocarcinoma (LUAD) is a study that examines the prognostic value of lactate metabolism genes in tumor cells, which are associated with clinical prognosis. We analyzed the expression and clinical data for LUAD from The Cancer Genome Atlas database, using the GSE68465 dataset from the Gene Expression Omnibus and the MSigDB database. LASSO Cox regression and stepwise Cox regression were used to identify the optimal lactate metabolism gene signature. Differences in immune infiltration, tumor mutation burden (TMB), and response to immune checkpoint blockade (ICB) therapy were evaluated between groups. LASSO and Cox regression analyses showed an eight-lactate metabolism gene signature for model construction in both TCGA cohort and GSE68465 data, with higher survival outcomes in high-risk groups. The lactate metabolism risk score had an independent prognostic value (hazard ratio: 2.279 [1.652-3.146], P < .001). Immune cell infiltration differed between the risk groups, such as CD8+ T cells, macrophages, dendritic cells, mast cells, and neutrophils. The high-risk group had higher tumor purity, lower immune and stromal scores, and higher TMB. High-risk samples had high tumor immune dysfunction and exclusion (TIDE) scores and low cytolytic activity (CYT) scores, indicating a poor response to ICB therapy. Similarly, most immune checkpoint molecules, immune inhibitors/stimulators, and major histocompatibility complex (MHC) molecules were highly expressed in the high-risk group. The 8-lactate metabolism gene-based prognostic model predicts patient survival, immune infiltration, and ICB response in patients with LUAD, driving the development of therapeutic strategies to target lactate metabolism.

Differential effect of plakoglobin in restoring the tumor suppressor activities of p53-R273H vs. p53-R175H mutants.

The six most common missense mutations in the DNA binding domain of p53 are known as "hot spots" and include two of the most frequently occurring p53 mutations (p53-R175H and p53-R273H). p53 stability and function are regulated by various post-translational modifications such as phosphorylation, acetylation, sumoylation, methylation, and interactions with other proteins including plakoglobin. Previously, using various carcinoma cell lines we showed that plakoglobin interacted with wild-type and several endogenous p53 mutants (e.g., R280K, R273H, S241F, S215R, R175H) and restored their tumor suppressor activities in vitro. Since mutant p53 function is both mutant-specific and cell context-dependent, we sought herein, to determine if plakoglobin tumor suppressive effects on exogenously expressed p53-R273H and p53-R175H mutants are similarly maintained under the same genetic background using the p53-null and plakoglobin-deficient H1299 cell line. Functional assays were performed to assess colony formation, migration, and invasion while immunoblotting and qPCR were used to examine the subcellular distribution and expression of specific proteins and genes that are typically regulated by or regulate p53 function and are altered in mutant p53-expressing cell lines and tumors. We show that though, plakoglobin interacted with both p53-R273H and p53-R175H mutants, it had a differential effect on the transcription and subcellular distribution of their gene targets and their overall oncogenic properties in vitro. Notably, we found that plakoglobin's tumor suppressive effects were significantly stronger in p53-R175H expressing cells compared to p53-R273H cells. Together, our results indicate that exploring plakoglobin interactions with p53-R175H may be useful for the development of cancer therapeutics focused on the restoration of p53 function.

The baseline hemoglobin level is a positive biomarker for immunotherapy response and can improve the predictability of tumor mutation burden for immunotherapy response in cancer.

Because only a subset of cancer patients can benefit from immunotherapy, identifying predictive biomarkers of ICI therapy response is of utmost importance. We analyzed the association between hemoglobin (HGB) levels and clinical outcomes in 1,479 ICIs-treated patients across 16 cancer types. We explored the dose-dependent associations between HGB levels and survival and immunotherapy response using the spline-based cox regression analysis. Furthermore, we investigated the associations across subgroups of patients with different clinicopathological characteristics, treatment programs and cancer types using the bootstrap resampling method. HGB levels correlated positively with clinical outcomes in cancer patients receiving immunotherapy but not in those without immunotherapy. Moreover, this association was independent of other clinicopathological characteristics (such as sex, age, tumor stage and tumor mutation burden (TMB)), treatment program and cancer type. Also, this association was independent of the established biomarkers of immunotherapy response, including TMB, PD-L1 expression and microsatellite instability. The combination of TMB and HGB level are more powerful in predicting immunotherapy response than TMB alone. Multi-omics analysis showed that HGB levels correlated positively with antitumor immune signatures and negatively with tumor properties directing antitumor immunosuppression, such as homologous recombination defect, stemness and intratumor heterogeneity. The HGB measure has the potential clinical value as a novel biomarker of immunotherapy response that is easily accessible from clinically routine examination. The combination of TMB and HGB measures have better predictive performance for immunotherapy response than TMB.

Predicting somatic mutation origins in cell-free DNA by semi-supervised GAN models

MotivationDistinguishing between pathogenic cancer-associated mutations and other somatic variants present in cell-free DNA (cfDNA) is one of the challenges in the field of liquid biopsy. This distinction is critical, since the misclassification of mutations stemming from clonal hematopoiesis (CH) as tumor-derived and vice versa could result in inaccurate diagnoses and inappropriate therapeutic interventions for patients. ResultsWe addressed this by developing a specialized machine learning technique to differentiate tumor- or CH-related mutations in cfDNA. We established a comprehensive in-house reference catalog, comprising approximately 25,000 single nucleotide variants (SNVs), each linked to either tumor or CH origin. This reference serves as a foundation for training a deep learning model, which is structured on the semi-supervised generative adversarial network (SSGAN) architecture. By analyzing genomic coordinates and nucleotide composition of cfDNA variants, our model attains 95 % area under the curve (AUC) in classifying uncharacterized variants as CH or tumor-derived. In conclusion, our research emphasizes the potential of genomic feature prediction, using cfDNA data, to stand as a robust alternative to conventional multi-analyte sequencing methods. This approach not only enhances the accuracy of distinguishing CH from tumor mutations in liquid biopsy data, but also highlights the potential of advanced data analysis techniques and machine learning in genomics and personalized medicine. Availability: https://github.com/FPalizban/SSGAN.

Assessing outcomes for patients receiving chemotherapy in the intensive care unit.

190 Background: Despite the low in-hospital mortality rate (9%) for Intensive Care Unit (ICU) stays in the US, outcomes for patients with cancer undergoing chemotherapy in the ICU remains unclear. We aimed to assess survival in patients with cancer (liquid, solid tumor and allogeneic stem cell transplant (alloSCT) receiving chemotherapy at our institution and identify patient characteristics for enhanced chemotherapy stewardship. Methods: We analyzed pharmacy data for patients with confirmed malignancies who received chemotherapy while admitted to the ICU at our institution from 1/1/21 to 12/31/23, excluding non-cancer patients and those on home oral regimens. Primary endpoints included 14-day, 30-day, and 90-day survival. Secondary analyses examined survival differences by age, ECOG performance status, and treatment history. Survival differences among patient subtypes were evaluated using Z-tests. Results: We identified 74 unique patients who received chemotherapy for cancer. 54 had liquid tumors, 5 were post-alloSCT, and 15 had solid tumors. The 90-day survival rate was 47% overall: 46% for the liquid tumor group, 80% for the alloSCT group, and 40% for the solid tumor group. When further stratified by tumor type, higher 90-day survival was variable; see Table 1 for details). In patients with lung cancer, 90-day survival was worse for non-small cell lung cancer without tumor mutations (0%, n=2) than those with targetable mutations (50%, n=4) or small cell lung cancer (33%, n=3). An ECOG performance status of 3-4 showed poorer 90-day survival in liquid tumors (23%) compared to ECOG 1-2 (74%; 95% CI 0.26 , 0.76). Solid tumors showed no significant ECOG differences (50%, 40%). Treatment-naive status showed higher 90-day survival in liquid tumors (59%) compared to treatment-resistant tumors (18%; 95% CI 0.17, 0.65), but not in solid tumors (50%, 20%). Conclusions: Our findings suggest generally unfavorable 90-day outcomes for ICU chemotherapy patients, especially those aged over 75, with multiple therapy lines, or ECOG status 3-4. Survival rates varied significantly across tumor types. We are currently broadening our study to include all solid tumor cancer patients. While this is a limited sample, this underscores the need for careful chemotherapy stewardship and advanced care planning in ICU settings. 90-day survival of solid and liquid tumor patients receiving chemotherapy in the ICU by select cancer diagnoses. Cancer Diagnosis n 90-Day Survival (%) AML 20 45 DLBCL 16 33 APML 6 83 Multiple myeloma 5 60 Other liquid tumors 1 11 45 Lung cancer 9 44 Germ cell tumor 2 100 Hormone-sensitive breast cancer 1 100 Other solid tumors 2 3 0 1 T-cell lymphoma, ALL, CNS lymphoma, Castleman, MPN, and plasmablastic lymphoma. Note, patients with allogenic stem cell transplants not included. 2 Carcinoma of unknown primary, colon adenocarcinoma, multiple solid tumors.

Detection and Interpretation of Clonal Hematopoiesis Variants during Routine Solid Tumor Next-Generation Sequencing: A Single-Institution Experience

Clonal hematopoiesis (CH) and Clonal Cytopenia of Undetermined Significance (CCUS) are recently recognized diagnostic entities that serve as an independent risk factor for cardiovascular disease and myeloid malignancy. CH is an incidental finding and evaluation of the incidence of CH/CCUS associated mutations in solid tumor Next Generation Sequencing (NGS) samples was undertaken to better understand the prevalence of mutations in this population. A retrospective review of clinical sequencing data for solid tumor malignancies diagnosed February 2022-April 2023 on NGS data was performed. Cases were reviewed for variants in genes associated with CH/CCUS. Variant allele frequencies and other factors of the sequencing data were assessed for determining risk of CH/CCUS. 2,479 cases were evaluated during the study period. Of these, 29 cases demonstrated potential CH/CCUS associated mutations with a total of 33 variants identified. These were identified in a variety of tumor types, with gliomas being the most common. Significant cardiac histories were found in over half of cases identified and few cases had abnormal blood counts. Detailed criteria for flagging variants as suspicious for CH and recommend these criteria as future guidelines for reporting are described. These variants are incidental findings which require more extensive follow up or change in therapy management utilizing a single institutional cohort.

7312 Tumor Size and Mutation Prevalence in Black Americans with Primary Aldosteronism

7312 Tumor Size and Mutation Prevalence in Black Americans with Primary Aldosteronism

Characterization of prognostic signature related with twelve types of programmed cell death in lung squamous cell carcinoma

ObjectiveThis study aimed to develop a prognostic cell death index (CDI) based on the expression of genes related with various types of programmed cell death (PCD), and to assess its clinical relevance in lung squamous cell carcinoma (LUSC).MethodsPCD-related genes were gathered and analyzed in silico using the transcriptomic data from the LUSC cohorts of The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Differentially expressed PCD genes were analyzed, and a prognostic model was subsequently constructed. CDI scores were calculated for each patient, and their correlations with clinical features, survival outcomes, tumor mutation burden, gene clusters, and tumor microenvironment were investigated. Unsupervised consensus clustering was performed based on CDI model genes. Furthermore, the correlation of CDI for sensitivity of targeted drugs, chemotherapy efficacy, and immunotherapy responses was assessed.ResultsBased on 351 differentially expressed PCD genes in LUSC, a CDI signature comprising FGA, GAB2, JUN, and CDKN2A was identified. High CDI scores were significantly associated with poor survival outcomes (p < 0.05). Unsupervised clustering revealed three distinct patient subsets with varying survival rates. CDKN2A exhibited significantly different mutation patterns between patients with high and low CDI scores (p < 0.01). High CDI scores were also linked to increased immune cell infiltration of specific subsets and altered expression of immune-related genes. Patients with high-CDI showed reduced sensitivity to several chemotherapeutic drugs and a higher Tumor Immune Dysfunction and Exclusion (TIDE) score, indicating potential resistance to immunotherapy.ConclusionThe CDI signature based on PCD genes offers valuable prognostic insights into LUSC, reflecting molecular heterogeneity, immune microenvironment associations, and potential therapeutic challenges. The CDI holds potential clinical utility in predicting treatment responses and guiding the selection of appropriate therapies for patients with LUSC. Future studies are warranted to further validate the prognostic value of CDI in combination with clinical factors and to explore its application across diverse patient cohorts.

Comprehensive Genomic Assessment of Advanced-Stage GI Stromal Tumors Using the Japanese National Center for Cancer Genomics and Advanced Therapeutics Database.

Clinical utility of comprehensive genomic profiling (CGP) for precision medicine has become evident. Although there are several reports on the genomic landscape of GI stromal tumors (GISTs), large-scale data specific to GIST are limited, especially in Asia. Additionally, the applicability of molecular-targeted agents identified using CGP has not been extensively examined. We investigated the status of genomic alterations in Japanese patients with advanced GISTs using the National Center for Cancer Genomics and Advanced Therapeutics (C-CAT) database to identify novel treatment strategies and drug development. We retrospectively reviewed the clinical and CGP data of patients with advanced-stage GIST registered in the C-CAT database to assess the genomic landscape and potential actionable alterations. Data from 144 patients were reviewed. Oncogenic alterations were detected frequently in KIT (78%), CDKN2A (37%), CDKN2B (29%), RB1 (11%), STK11 (10%), TP53 (9%), PDGFRA (6%), and SDHB (6%). Loss of CDKN2A/CDKN2B was only observed in KIT/PDGFRA-mutated GISTs, while alterations in SDHA/SDHB were only detected in KIT/PDGFRA wild-type GISTs. Among 119 KIT/PDGFRA-mutated GISTs, 95 (80%) had oncogenic genomic alterations and 29 (24%) had actionable alterations, excluding KIT and PDGFRA. However, among 25 KIT/PDGFRA wild-type GISTs, 22 (88%) had oncogenic alterations and 11 (44%) had actionable alterations. Representative candidate drugs for genome-matched therapies in KIT/PDGFRA-mutated and wild-type GISTs were as follows: pembrolizumab for tumor mutation burden-high in one and two patients, respectively; poly-adenosine diphosphate ribose polymerase inhibitors for alterations related to homologous recombination deficiency in 12 and one patient, respectively; NTRK inhibitor for ETV6-NTRK3 fusion in one with KIT/PDGFRA wild-type GIST; and human epidermal growth factor receptor 2-antibody-drug conjugate in one with KIT/PDGFRA-mutated GIST. This study highlights the genomic landscape of advanced GISTs and the important role of CGP in identifying rational molecular-targeted therapeutic options.

Molecular landscape of ERBB2 alterations in 3000 advanced NSCLC patients

ERBB2 (HER2) represents a newly recognized actionable oncogenic driver in non-small cell lung cancer (NSCLC), with approved targeted therapy available. Understanding the landscape of ERBB2 alterations and co-occurring mutations is essential for guiding treatment decisions. We conducted an analysis involving 3000 NSCLC patients with all types of ERBB2 alterations, drawn from two extensive retrospective cohorts: 1281 from Geneplus (Chinese) and 1719 from Guardant360 (the United States, US). The incidence of all types of ERBB2 alterations was found to be 5.6% in the Chinese group and 5.2% in the US group. In both cohorts, among oncogenic alterations of ERBB2, exon 20 insertion Y772_A775dupYVMA was the most frequent alteration (58% vs 41.6% in the Chinese vs the US), followed by G776delinsVC/LC/VV/IC (10.7% vs 9.7%), and S310X (10.5% vs 15.4%). EGFR ex20 insertions were identified in the A767-V774 region, whereas ERBB2 ex20 insertions were observed in the Y772-P780 region. Notably, EGFR ex20 insertions exhibited greater insertion diversity. Clinical characteristics of EGFR and ERBB2 ex20 NSCLC were similar, characterized by low tumor mutation burden (TMB), a predominant never-smoker population, and a majority of lung adenocarcinoma cases.

Unlocking the Potential of Disulfidptosis-Related LncRNAs in Lung Adenocarcinoma: A Promising Prognostic LncRNA Model for Survival and Immunotherapy Prediction.

Disulfidptosis was stimulated in high SLC7A11 expression cells starving to glucose. We attempted to identify disulfidptosis-related lncRNAs (DRLs), built a prognostic model to predict survival, and analyzed the tumor microenvironment. The TCGA database was utilized to procure the pertinent data. By utilizing both Cox regression and the least absolute shrinkage and selection operator (LASSO) method, a risk model based on DRLs was formulated for prognostic evaluation. The ability of survival prediction was validated by multiple approaches. The biological functions were screened through GO, KEGG, and GSEA. Various methods were employed to evaluate the tumor immune environment, which included ESTIMATE, tumor mutation burden (TMB) score, CIBERSORT algorithm, and tumor immune dysfunction and exclusion (TIDE) score. Ninety-one DRLs were recognized, and lncRNA AC092718.4, AL365181.2, AL606489.1, EMSLR, and ENTPD3-AS1 were involved in the risk model. The GEO database was used to verify the influence of these lncRNAs on survival. The following analyses showed that survival could be predicted excellently by the DRLs risk model. The results of enrichment analyses pointed toward the involvement of the cell cycle and IgA production pathways. In the low-risk patient group, there was a notable surge in stromal, immune, and ESTIMATE scores, while the TMB scores took a tumble. Conversely, the high-risk patient group displayed a converse trend. Notably, the group of patients with lower risk scores and higher TMB scores showed the most favorable survival outcomes, underscoring the importance of considering both risk score and TMB in predicting the response to immune checkpoint blockade therapy. Furthermore, patients classified as high-risk might display resistance to both chemotherapy and targeted therapy. Cellular biological experiments proved that lncRNA AC092718.4 promoted invasion, migration, and proliferation abilities invitro. These results provided valuable insights into the role of DRLs in LUAD and presented a possible effective treatment approach for LUAD. We developed a disulfidptosis-related risk model with 5 lncRNAs that enables survival prediciton for LUAD patients and aids cilinical decisions by forecasting the TME, TMB, and drug sensitivity, making it a valuable tool for outcomes prediction.

Comprehensive evaluation of immunological attributes and immunotherapy responses of positive T cell function regulators in colorectal cancer

BackgroundPositive regulators of T-cell function (PTFRs), integral to T-cell proliferation and activation, have been identified as potential prognostic markers in colorectal cancer (CRC). Despite this, their role within the tumor microenvironment (TME) and their response to immunotherapy are not yet fully understood.MethodsThis study delved into PTFR-related CRC subtypes by analyzing four independent transcriptome datasets, emphasizing the most significant prognostic PTFRs. We identified differentially expressed genes (DEGs) between two subtypes and developed a PTFR risk model using LASSO and Cox regression methods. The model’s associations with survival time, clinical features, TME characteristics, tumor mutation profiles, microsatellite instability (MSI), cancer stem cell (CSC) index, and responses to chemotherapy, targeted therapy, and immunotherapy were subsequently explored.ResultsThe PTFR risk model demonstrated a strong predictive capacity for CRC. It facilitated the estimation of immune cell composition, HLA expression levels, immune checkpoint expression, mutation burden, CSC index features, and the effectiveness of immunotherapy.ConclusionsThis study enhances our understanding of the role of PTFRs in CRC progression and introduces an innovative assessment framework for CRC immunotherapy. This framework improves the prediction of treatment outcomes and aids in the customization of therapeutic strategies.

Solar elastosis correlates with high tumor mutation burden and better 5-year disease-specific survival in patients with stage II/III melanoma

ObjectiveTo evaluate the relation between solar elastosis and tumor mutation burden (TMB) in a large clinically annotated cohort of stage II and III melanoma patients. MethodsPrimary cutaneous melanomas from 469 AJCC (8th edition) stage II and III patients with clinical annotation including outcome at 5 years of diagnosis were histopathologically evaluated for solar elastosis. Next-generation sequencing assay MSK-IMPACTTM was employed to determine TMB. Analysis by Fisher’s exact test, chi-square, and Kruskal-Wallis were performed, as well as uni- and multivariate logistic regression. ResultsTumors stratified by low and high TMB showed marked and statistically significant differences in presence and extent of associated solar elastosis. Lower risk patient stage (II versus III by AJCC 8th edition) as well as better 5-year melanomaspecific survival (as binary variable of controls-survivors versus cases-dead of disease at 5 years of diagnosis) were associated with severe solar elastosis. On univariate and multivariate logistic regression models, severe solar elastosis predicted significantly decreased odds of dying of melanoma within 5 years of diagnosis (OR 0.60, 95% CI 0.39-0.89; and OR 0.42, 95% CI 0.20-0.83, respectively; both p<0.05) ConclusionThe association of solar elastosis to TMB and 5-year melanoma specific survival points to its potential as a biomarker of clinical relevance that can be assessed by routine histopathology.

Germline Human Leukocyte Antigen Status is Associated With Immunotherapy-Induced Pneumonitis and Treatment Response in Patients With Non–Small Cell Lung Carcinoma With High Programmed Death-Ligand 1 Expression

IntroductionThe germline human leukocyte antigen (HLA) status has been found to be associated with immunotherapy outcomes in patients with NSCLC, but its correlation to immunotherapy-induced pneumonitis and prognostic impact in the Asian population remains largely unknown. MethodsWe evaluated the HLA genotype of the germline and available tumor samples in 42 patients with programmed death-ligand 1 expression of 50% or higher undergoing pembrolizumab immunotherapy. The HLA allele expression was correlated with tumor response, disease survival, and the occurrence of pneumonitis. ResultsIt was observed that the germline HLA-C homozygosity and HLA-DRB1∗13 expression were related to a worse progression-free survival and treatment response. Importantly, all patients (7/7 patients) who developed pneumonitis in our cohort expressed the HLA-DPB1∗02 allele, and the incidence of pneumonitis was 31.8% (7/22 patients) in patients expressing this allele compared with 0% (0/20 patients) in those without this allele (p = 0.009). Investigation of the tumor samples from 15 patients revealed some degree of HLA loss in the HLA class I loci in 40% (6/15) of patients, and no significant difference in tumor mutation burden was found among patients with different treatment responses. ConclusionTaken together, this study evaluated the impact of HLA status in both germline and tumor samples in patients with NSCLC with high programmed death-ligand 1 expression, and the high incidence of immunotherapy-induced pneumonitis in patients expressing the HLA-DPB1∗02 allele may suggest a routine HLA typing and closer monitoring in this patient subset.

Immune Subtypes and Characteristics of Endometrial Cancer Based on Immunogenes.

The aim of this study was to explore the immune subtypes of endometrial cancer (EC) and its characteristics by immunogenes from the perspective of multidimensional genomics (multi-omics). Immune subtypes were carried out using an unsupervised non-negative matrix factorization clustering (NMF) method and their characteristics were analysed. Key genes were identified using random forest analysis. A predictive model for immune subtypes and their clinical prognosis were constructed. The relationship between immune subtypes and molecular subtypes was investigated. Two immune subtypes C1 and C2 were available. C2 patients were younger, less graded, had significantly higher immune cell infiltration, immune checkpoint expression, tumor neoantigens, tumor mutation load than C1 (P<005). S100A9, CD3D, CD3E, HLA-DRB1 and IL2RB were the key genes with significant survival outcomes. S100A9 expression was lower in C2 than C1, and IL2RB, HLA-DRB1, CD3E and CD3D expression was higher than C1 (P<0.05). The predictive accuracy of five key genes for immune subtypes was good, with a Receiver operating characteristic of 0.941. The incidence of TP53abn type in C2 was significantly lower than that of C1, and the incidence of POLE type was significantly higher than that of C1 (P<0.0001). EC can be divided into two immune subtypes based on immunogenes. Low expression of S100A9 and high expression of IL2RB, HLA-DRB1, CD3E, and CD3D suggest sensitivity to immunotherapy and a good prognosis.

MHC class II genotypes are independent predictors of anti-PD1 immunotherapy response in melanoma.

Immune checkpoint blockade is a highly successful anti-cancer immunotherapy. Both CTLA4 and PD1 checkpoint blockers are clinically available for melanoma treatment, with anti-PD1 therapy reaching response rates of 35-40%. These responses, which are mediated via neoantigen presentation by the polymorphic MHC complex, are hard to predict and the tumor mutation burden is currently one of the few available biomarkers. While MHC genotypes are expected to determine therapy responses, association studies have remained largely elusive. We developed an overall MHC genotype binding score (MGBS), indicative of a patient's MHC class I (MHC-I) and class II (MHC-II) neoantigen binding capacity and solely based on the germline MHC-I (MGBS-I) and MHC-II (MGBS-II) genotypes. These scores were then correlated to survival and clinical responses following anti-PD1 immunotherapy in a previously published dataset of 144 melanoma patients. We demonstrate that MGBS scores are TMB-independent predictors of anti-PD1 immunotherapy responses in melanoma. Opposite outcomes were found for both MHC classes, with high MGBS-I and MGBS-II predicting good and bad outcomes, respectively. Interestingly, high MGBS-II is mainly associated with treatment response failure in a subgroup of anti-CTLA4 pretreated patients. Our results suggest that MGBS, calculated solely from the MHC genotype, has clinical potential as a non-invasive and tumor-independent biomarker to guide anti-cancer immunotherapy in melanoma.