Association of PTPRD/PTPRT Mutation With Better Clinical Outcomes in NSCLC Patients Treated With Immune Checkpoint Blockades

System analysis based on T-cell exhaustion-related genes identifies PTPRT as a promising diagnostic and prognostic biomarker for gastric cancer

Multiple investigations have demonstrated the crucial involvement of T-cell exhaustion (TEX) in anti-tumor immune response and their strong correlation with prognosis. This study aimed at creating a strong signature using TEX for gastric cancer through bioinformatics analysis and experimental validation. We utilized data from The Cancer Genome Atlas (TCGA) databases to retrieve RNA-seq data from patients with stomach adenocarcinoma (STAD). Genes related to TEX were discovered using gene set variance analysis (GSVA) and weighted gene correlation network analysis (WGCNA). Subsequently, prognostic signature based on TEX was developed using LASSO-Cox analysis. Relationship between key genes and immune cells were examined. Finally, biological function of a key TEX-related gene PTPRT in gastric cancer was verified by in vivo experiment. A total of 29 TEX-related biomarkers were screened by WGCNA and random forest. Among them, five core signatures (PTPRT, CAV2, PPIH, PRDM2, and FGF1), further identified by LASSO-Cox, were considered as strong predictors of prognosis for gastric cancer and associated with immune infiltration. PTPRT gene had the largest number of SNPs, with the most mutation types. In vivo experiments revealed that PTPRT overexpression significantly inhibited tumor malignant progression and accelerated apoptosis through stimulating the secretion of killer cytokines such as TNF-α and IFN-γ. In addition, flow cytometry revealed that PTPRT overexpression alleviated TEX by increasing the abundance of CD8+ T cells, with inhibition of cell surface PD-1 and Tim-3. The predictive prognostic value of TEX gene expression levels was evaluated in patients with gastric cancer, providing a new perspective for precision immuno-oncology studies.

PTPRT loss enhances anti-PD-1 therapy efficacy by regulation of STING pathway in non-small cell lung cancer

With the revolutionary progress of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer, identifying patients with cancer who would benefit from ICIs has become critical and urgent. Here, we report protein tyrosine phosphatase receptor type T (PTPRT) loss as a precise and convenient predictive marker independent of PD-L1 expression for anti-PD-1/PD-L1 axis therapy. Anti-PD-1/PD-L1 axis treatment markedly increased progression-free survival in patients with PTPRT-deficient tumors. PTPRT-deficient tumors displayed cumulative DNA damage, increased cytosolic DNA release, and higher tumor mutation burden. Moreover, the tyrosine residue 240 of STING was identified as a direct substrate of PTPRT. PTPRT loss elevated phosphorylation of STING at Y240 and thus inhibited its proteasome-mediated degradation. PTPRT-deficient tumors released more IFN-β, CCL5, and CXCL10 by activation of STING pathway and increased immune cell infiltration, especially of CD8 T cells and natural killer cells, ultimately enhancing the efficacy of anti-PD-1 therapy in multiple subcutaneous and orthotopic tumor mouse models. The response of PTPRT-deficient tumors to anti-PD-1 therapy depends on the tumor-intrinsic STING pathway. In summary, our findings reveal the mechanism of how PTPRT-deficient tumors become sensitive to anti-PD-1 therapy and highlight the biological function of PTPRT in innate immunity. Considering the prevalence of PTPRT mutations and negative expression, this study has great value for patient stratification and clinical decision-making.

Blood-based molecular and cellular biomarkers of early response to neoadjuvant PD-1 blockade in patients with non-small cell lung cancer

BACKGROUND

Despite the improved survival observed in PD-1/PD-L1 blockade therapy, a substantial proportion of cancer patients, including those with non-small cell lung cancer (NSCLC), still lack a response.

METHODS

Transcriptomic profiling was conducted on a discovery cohort comprising 100 whole blood samples, as collected multiple times from 48 healthy controls (including 43 published data) and 31 NSCLC patients that under treatment with a combination of anti-PD-1 Tislelizumab and chemotherapy. Differentially expressed genes (DEGs), simulated immune cell subsets, and germline DNA mutational markers were identified from patients achieved a pathological complete response during the early treatment cycles. The predictive values of mutational markers were further validated in an independent immunotherapy cohort of 1661 subjects, and then confirmed in genetically matched lung cancer cell lines by a co-culturing model.

RESULTS

The gene expression of hundreds of DEGs (FDR p < 0.05, fold change < -2 or > 2) distinguished responders from healthy controls, indicating the potential to stratify patients utilizing early on-treatment features from blood. PD-1-mediated cell abundance changes in memory CD4 + and regulatory T cell subset were more significant or exclusively observed in responders. A panel of top-ranked genetic alterations showed significant associations with improved survival (p < 0.05) and heightened responsiveness to anti-PD-1 treatment in patient cohort and co-cultured cell lines.

CONCLUSION

This study discovered and validated peripheral blood-based biomarkers with evident predictive efficacy for early therapy response and patient stratification before treatment for neoadjuvant PD-1 blockade in NSCLC patients.

KMT2C mutation as a predictor of immunotherapeutic efficacy in colorectal cancer

Immunotherapy had shown good antitumor activity in a variety of solid tumors, but low benefit in CRC, so there was an urgent need to explore new biomarkers. We evaluated the role of KMT2C using publicly available data from the Cancer Genome Atlas (TCGA) and Memorial Sloan Kettering Cancer Center (MSKCC). In addition, further analysis was performed in an internal cohort. Moreover, the mutant profiles of KMT2C was analyzed in a large CRC cohort. The relationship between clinical pathologic features and KMT2C were analyzed with using the two-sided chi-squared test or the Fisher exact test. Clinicopathologic characteristics associated with overall survival using Cox regression and the Kaplan-Meier method. We found that KMT2C-mutated CRC patients in the immunotherapy cohort had significantly improved OS compared with KMT2C WT patients (P = 0.013). However, this phenomenon did not exist in non-immunotherapy cohort. Our cohort validated the value of KMT2C mutations in predicting better clinical outcomes, including ORR (P < 0.0001) and OS (P = 0.010). Meanwhile, KMT2C mutation was associated with higher tumor mutation burden, MSI score, higher levels of immune-associated T cells, neutrophil, and M1-type macrophages. Our study suggested that KMT2C mutation might be a potential positive predictor for CRC immunotherapy.

Tumor cell-intrinsic SETD2 inactivation sensitizes cancer cells to immune checkpoint blockade through the NR2F1-STAT1 pathway

BACKGROUND

Cancer immunotherapies can induce durable tumor regression, but most patients do not respond. SETD2 mutation has been linked to the efficacy of immune checkpoint inhibitors (ICIs) immunotherapy. The functional importance of the SETD2 inactivation and how to modulate immunotherapy response remains unclear.

METHODS

To explore the function of SETD2 in immunotherapy, knockout and subsequent functional experiments were conducted. Bulk RNA-seq, ATAC-seq, Chip-seq and single-cell RNA-seq were performed to dissect the mechanism and explore the immune microenvironment of mouse tumor. Flow cytometry was used to assess cell surface antigen and intratumoral T cell levels.

RESULTS

We comprehensively determine the effect of SETD2 inactivation in ICIs therapy and elucidate the mechanistic impact on tumor immunity. Murine syngeneic tumors harboring Setd2 inactivation are sensitive to ICIs. By bulk and single-cell RNA-seq, we further reveal that SETD2 inactivation reprograms intratumoral immune cells and inflames the tumor microenvironment, which is characterized by high infiltration of T cells and enhanced antigen presentation to activate CD8+ T cell-mediated killing. Mechanistically, via an integrated multiomics analysis using ATAC-seq, ChIP-seq and RNA-seq, we demonstrate that SETD2 inactivation reduces NR2F1 transcription by impairing H3K36me3 deposition and chromatin accessibility, which activates the STAT1 signaling pathway to promote chemokines and programmed cell death protein-1 (PD-1) expression and enhance antigen presentation. All these regulatory mechanisms synergistically promote the effects of anti-programmed cell death ligand 1 immunotherapy in Setd2-knockout syngeneic mouse models. The SETD2-NR2F1-STAT1 regulatory axis is conserved in human and murine cancers. Finally, cancer patients harboring SETD2 mutations who received ICIs show increased durable clinical benefits and survival.

CONCLUSIONS

These findings provide novel insights into the biology of SETD2 inactivation regulation and reveal a new potential therapeutic biomarker for ICIs immunotherapy in various refractory cancers.

PTPRD mutation is a prognostic biomarker for sensitivity to ICIs treatment in advanced non-small cell lung cancer

BACKGROUND

Immune checkpoint inhibitors (ICIs) have become the standard treatment for advanced non-small cell lung cancer (NSCLC). ICIs can provide durable responses and prolong survival for some patients. With the increasing routine of next-generation sequencing (NGS) in clinical practice, it is essential to integrate prognostic factors to establish novel nomograms to improve clinical prediction ability in NSCLC with ICIs treatment.

METHODS

Clinical information, response data, and genome data of advanced NSCLC treated ICIs were obtained from cBioPortal. The top 20 gene alterations in durable clinical benefit (DCB) were compared with those genes in no durable benefit (NDB). Survival analyses were performed using the Kaplan-Meier plot method and selected clinical variables to develop a novel nomogram.

RESULTS

The mutation of PTPRD was significantly related to progression free survival (PFS) and overall survival (OS) in advanced NSCLC with ICIs treatment (PFS: p = 0.0441, OS: p = 0.0086). The PTPRD mutation was closely related to tumor mutational burden (TMB) and tumor-infiltrating immune cells (TIICs). Two novel nomograms were built to predict the PFS and OS of advanced NSCLC patients with ICIs treatment.

CONCLUSIONS

Our study suggested that PTPRD mutations could serve as a predictive biomarker for the sensitivity to ICIs treatment and PFS and OS in advanced NSCLC with ICIs. Our systematic nomograms showed great potential value in clinical application to predict the PFS and OS for advanced NSCLC patients with ICIs.

A 20-gene mutation signature predicts the efficacy of immune checkpoint inhibitor therapy in advanced non-small cell lung cancer patients

BACKGROUND

There is an unmet need to identify novel predictive biomarkers that enable more accurate identification of individuals who can benefit from immune checkpoint inhibitor (ICI) therapy. The US FDA recently approved tumor mutational burden (TMB) score of ≥ 10 mut/Mb as a threshold for pembrolizumab treatment of solid tumors. Our study aimed to test the hypothesis that specific gene mutation signature may predict the efficacy of ICI therapy more precisely than high TMB (≥ 10).

METHODS

We selected 20 candidate genes that may predict for the efficacy of ICI therapy by the analysis of data from a published cohort of 350 advanced non-small cell lung cancer (NSCLC) patients. Then, we compared the influences of various gene mutation signatures on the efficacy of ICI treatment. They were also compared with PD-L1 and TMB. The Kaplan-Meier method was utilized to evaluate the prognosis univariates, while selected univariates were adopted to develop a systematic nomogram.

RESULTS

A high mutation signature, where three or more of the 20 selected genes were mutated, was associated with the significant benefits of ICI therapy. Specifically, patients with high mutation signature were confirmed to have better prognosis for ICI treatment, compared with those with wild type (the median PFS: 7.17 vs. 2.90 months, p = 0.0004, HR = 0.47 (95% [CI]:0.32-0.68); the median OS: unreached vs. 9 months, p = 1.8E-8, HR = 0.17 (95% [CI]:0.11-0.25)). Moreover, those patients with the high mutation signature achieved significant ICI treatment benefits, while there was no difference of OS and PFS between patients without the signature but TMB-H (≥ 10) and those without the signature and low TMB(< 10). Finally, we constructed a novel nomogram to evaluate the efficacy of ICI therapy.

CONCLUSION

A high mutational signature with 3 or more of the 20-gene panel could provide more accurate predictions for the outcomes of ICI therapy than TMB ≥ 10 in NSCLC patients.

Screening marker genes of type 2 diabetes mellitus in mouse lacrimal gland by LASSO regression

Type 2 diabetes mellitus (T2DM) is characterized by insulin resistance and a relative deficiency of insulin. This study aims to screen T2DM-related maker genes in the mouse extraorbital lacrimal gland (ELG) by LASSO regression.C57BLKS/J strain with leptin db/db homozygous mice (T2DM, n = 20) and wild-type mice (WT, n = 20) were used to collect data. The ELGs were collected for RNA sequencing. LASSO regression was conducted to screen marker genes with the training set. Five genes were selected from 689 differentially expressed genes by LASSO regression, including Synm, Elovl6, Glcci1, Tnks and Ptprt. Expression of Synm was downregulated in ELGs of T2DM mice. Elovl6, Glcci1, Tnks, and Ptprt were upregulated in T2DM mice. Area under receiver operating curve of the LASSO model was 1.000(1.000-1.000) and 0.980(0.929-1.000) in the training set and the test set, respectively. The C-index and the robust C-index of the LASSO model were 1.000 and 0.999, respectively, in the training set, and 1.000 and 0.978, respectively, in the test set. In the lacrimal gland of db/db mice, Synm, Elovl6, Glcci1, Tnks and Ptprt can be used as marker genes of T2DM. Abnormal expression of marker genes is related to lacrimal gland atrophy and dry eye in mice.

Hereditable variants of classical protein tyrosine phosphatase genes: Will they prove innocent or guilty?

Protein tyrosine phosphatases, together with protein tyrosine kinases, control many molecular signaling steps that control life at cellular and organismal levels. Impairing alterations in the genes encoding the involved proteins is expected to profoundly affect the quality of life-if compatible with life at all. Here, we review the current knowledge on the effects of germline variants that have been reported for genes encoding a subset of the protein tyrosine phosphatase superfamily; that of the thirty seven classical members. The conclusion must be that the newest genome research tools produced an avalanche of data that suggest 'guilt by association' for individual genes to specific disorders. Future research should face the challenge to investigate these accusations thoroughly and convincingly, to reach a mature genotype-phenotype map for this intriguing protein family.

Interplay between Tumor Mutational Burden and Mutational Profile and Its Effect on Overall Survival: A Pilot Study of Metastatic Patients Treated with Immune Checkpoint Inhibitors

Purpose: Solid tumors harboring tumor mutational burden (TMB) ≥10 mutations per megabase (mut/Mb) received agnostic approval for pembrolizumab. This work aims to analyze the somatic mutational profile’s influence on the outcomes of patients with TMB-high tumors treated with immune checkpoint inhibitors (ICIs). Methods: This post-hoc analysis evaluated clinical and molecular features of patients with solid tumors treated with ICIs that could be either monoclonal antibody directed against programmed cell death protein-1 or monoclonal antibody directed against programmed cell death ligand 1 (anti-PD-1/anti-PD-L1), monoclonal antibody directed against cytotoxic T lymphocyte-associated antigen (anti-CTLA-4) or a combined treatment regimen including one anti-PD-1/anti-PD-L1 and one anti-CTLA-4 (ICIs combination). We performed OS analysis for TMB thresholds of ≥10, ≥20, and <10 mut/Mb. We assessed OS according to the mutational profile for a TMB ≥ 10 mut/Mb cutoff. For genes correlated with OS at the univariate assessment, we conducted a Cox multivariate analysis adjusted by median TMB, sex, age, microsatellite instability (MSI), and histology. Results: A total of 1661 patients were investigated; 488 with a TMB ≥10 mut/Mb (29.4%). The median OS was 42 months for TMB ≥10 or 20 mut/Mb, and 15 months for TMB <10 mut/Mb (p < 0.005). Among TMB ≥10 mut/Mb patients, mutations in E2F3 or STK11 correlated with worse OS, and mutations in NTRK3, PTPRD, RNF43, TENT5C, TET1, or ZFHX3 with better OS. These associations were confirmed with univariate and multivariate analyses (p < 0.05). Melanoma histology and TMB above the median endowed patients with better OS (p < 0.05), while MSI status, age, and gender did not have a statistically significant effect on OS. Conclusion: Combining TMB and mutation profiles in key cancer genes can better qualify patients for ICI treatment and predict their OS.

PTPRD/PTPRT mutation as a predictive biomarker of immune checkpoint inhibitors across multiple cancer types

Background

Immune checkpoint inhibitors (ICIs) are dramatically changing the treatment landscape of a variety of cancers. Nevertheless, the variability in ICI responses highlight the importance in identifying predictive biomarkers. PTPRD and PTPRT (PTPRD/PTPRT) are the phosphatases of JAK-STAT signaling, a critical pathway in anti-cancer immunity regulation. However, the pan-cancer association between PTPRD/PTPRT mutation and the efficacy of ICIs remains unclear across pan-cancer patients.

Methods

We analyzed the association between PTPRD/PTPRT mutations and patient outcomes using clinical data and genomic mutations from TCGA pan-cancer cohort. Furthermore, the ICI-treatment cohort was used to evaluate the relationship between PTPRD/PTPRT mutation and the efficacy of ICIs. Another ICIs-treatment cohort was used to validate the findings. The TCGA pan-cancer dataset was analyzed to explore the correlation between PTPRD/PTPRT mutations and immune signatures. Moreover, we combined four factors to construct a nomogram model that could be used to predict the survival of pan-cancer patients receiving ICI treatment. The calibration curves and area under the curve were applied to assess the performance of the model.

Results

PTPRD/PTPRT mutations were shown to be associated with a worse prognosis in TCGA cohort (P < 0.05). In the Samstein cohort, prolonged overall survival (OS) was observed in PTPRD/PTPRT mutant cancers, compared with wild-type cancers (mOS: 40.00 vs 16.00 months, HR = 0.570, 95%CI: 0.479-0.679, P < 0.0001). In the validation cohort, significant OS advantage was observed in PTPRD/PTPRT mutant patients (mOS: 31.32 vs 15.53 months, HR = 0.658, 95%CI: 0.464-0.934, P = 0.0292). Furthermore, PTPRD/PTPRT mutations were associated with a higher tumor mutational burden, MSI score, and TCR score (P < 0.0001). Enhanced immune signatures were found in the PTPRD/PTPRT mutant cancers (P < 0.05). Finally, we successfully established a nomogram model that could be used to predict the survival of NSCLC patients who received ICI treatment. Based on the risk score of the model, patients in the low-risk group showed a better mOS than those in the high-risk group (mOS: 2.75 vs 1.08 years, HR = 0.567, 95%CI: 0.492-0.654; P < 0.001).

Conclusions

PTPRD/PTPRT mutations may be a potential biomarker for predicting ICI treatment responsiveness in multiple cancer types.

Case Report: Clinical complete response of advanced renal cell carcinoma associated with Xp11.2 translocation/TFE3 gene fusion by treated by camrelizumab and axitinib: A rare case report

Renal cell carcinoma (RCC) associated with Xp11.2 translocation/TFE3 gene fusions is a rare subtype of renal tumor. This entity predominantly occurs in juveniles, but rarely in adults. Xp11.2 translocation RCC (tRCC) patients with lymph node or organ metastasis are associated with poor prognosis, and the strategy remains controversial. Herein, we presented our experience with the diagnosis and treatment of an adult case of Xp11.2 tRCC. In our clinical practice, a 32-year-old male manifested fever and right flank paroxysmal blunt pain, and computed tomography showed an inhomogeneous mass, 6 cm in diameter, in the right kidney. Then right partial nephrectomy (PN) and renal hilar lymph node dissection by laparoscopic surgery were performed. Pathology revealed that the tumor cells were positive for TFE3 immunohistologically and positive for TFE3 break-apart fluorescence in situ hybridization assay. A splice site mutation c.1544-1G>T of protein tyrosine phosphatase receptor delta (PTPRD) was detected by next-generation sequencing and weak PTPRD expression was confirmed in tumor tissues compared to tumor periphery. This patient was diagnosed with stage III RCC and received immune checkpoint inhibitor (camrelizumab) in combination with tyrosine kinase inhibitor (axitinib) treatment for 1 year. He achieved a clinical complete response with no sign of recurrence or metastasis. PTPRD mutation might be a favorable indicator for Xp11.2 tRCC patients managed by PN and followed by the adjuvant therapy of immune checkpoint inhibitor and tyrosine kinase inhibitor.

Novel GIRlncRNA Signature for Predicting the Clinical Outcome and Therapeutic Response in NSCLC

Background: Non–small cell lung cancer (NSCLC) is highly malignant with driver somatic mutations and genomic instability. Long non-coding RNAs (lncRNAs) play a vital role in regulating these two aspects. However, the identification of somatic mutation-derived, genomic instability-related lncRNAs (GIRlncRNAs) and their clinical significance in NSCLC remains largely unexplored.

Methods: Clinical information, gene mutation, and lncRNA expression data were extracted from TCGA database. GIRlncRNAs were screened by a mutator hypothesis-derived computational frame. Co-expression, GO, and KEGG enrichment analyses were performed to investigate the biological functions. Cox and LASSO regression analyses were performed to create a prognostic risk model based on the GIRlncRNA signature (GIRlncSig). The prediction efficiency of the model was evaluated by using correlation analyses with mutation, driver gene, immune microenvironment contexture, and therapeutic response. The prognostic performance of the model was evaluated by external datasets. A nomogram was established and validated in the testing set and TCGA dataset.

Results: A total of 1446 GIRlncRNAs were selected from the screen, and the established GIRlncSig was used to classify patients into high- and low-risk groups. Enrichment analyses showed that GIRlncRNAs were mainly associated with nucleic acid metabolism and DNA damage repair pathways. Cox analyses further identified 19 GIRlncRNAs to construct a GIRlncSig-based risk score model. According to Cox regression and stratification analyses, 14 risk lncRNAs (AC023824.3, AC013287.1, AP000829.1, LINC01611, AC097451.1, AC025419.1, AC079949.2, LINC01600, AC004862.1, AC021594.1, MYRF-AS1, LINC02434, LINC02412, and LINC00337) and five protective lncRNAs (LINC01067, AC012645.1, AL512604.3, AC008278.2, and AC089998.1) were considered powerful predictors. Analyses of the model showed that these GIRlncRNAs were correlated with somatic mutation pattern, immune microenvironment infiltration, immunotherapeutic response, drug sensitivity, and survival of NSCLC patients. The GIRlncSig risk score model demonstrated good predictive performance (AUCs of ROC for 10-year survival was 0.69) and prognostic value in different NSCLC datasets. The nomogram comprising GIRlncSig and tumor stage exhibited improved robustness and feasibility for predicting NSCLC prognosis.

Conclusion: The newly identified GIRlncRNAs are powerful biomarkers for clinical outcome and prognosis of NSCLC. Our study highlights that the GIRlncSig-based score model may be a useful tool for risk stratification and management of NSCLC patients, which deserves further evaluation in future prospective studies.

Patients deriving long-term benefit from immune checkpoint inhibitors demonstrate conserved patterns of site-specific mutations

Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy and are now the preferred treatment for several tumor types. Though ICIs have shown remarkable efficacy in several cancer histologies, in many cases providing long-term disease control, not all patients will derive clinical benefit from such approaches. Given the lack of a reliable predictive biomarker for therapeutic responses to ICIs, we conducted a retrospective analysis of publicly available genomic data from a large pan-cancer cohort of patients receiving ICI-based immunotherapy. Consistent with previous results, patients in the combined cohort deriving a long-term survival benefit from ICIs were more likely to have a higher tumor mutational burden (TMB). However, this was not uniform across tumor-types, failing to predict for long-term survivorship in most non-melanoma cancers. Interestingly, long-term survivors in most cancers had conserved patterns of mutations affecting several genes. In melanoma, this included mutations affecting TET1 or PTPRD. In patients with colorectal cancer, mutations affecting TET1, RNF43, NCOA3, LATS1, NOTCH3, or CREBBP were also associated with improved prognosis, as were mutations affecting PTPRD, EPHA7, NTRK3, or ZFHX3 in non-small cell lung cancer, RNF43, LATS1, or CREBBP mutations in bladder cancer, and VHL mutations in renal cell carcinoma patients. Thus, this study identified several genes that may have utility as predictive biomarkers for therapeutic responses in patients receiving ICIs. As many have no known relationship to immunotherapy or ICIs, these genes warrant continued exploration, particularly for cancers in which established biomarkers such as PD-L1 expression or TMB have little predictive value.

Cell-Free DNA for Genomic Analysis in Primary Mediastinal Large B-Cell Lymphoma

High-throughput sequencing of cell-free DNA (cfDNA) has emerged as a promising noninvasive approach in lymphomas, being particularly useful when a biopsy specimen is not available for molecular analysis, as it frequently occurs in primary mediastinal large B-cell lymphoma (PMBL). We used cfDNA for genomic characterization in 20 PMBL patients by means of a custom NGS panel for gene mutations and low-pass whole-genome sequencing (WGS) for copy number analysis (CNA) in a real-life setting. Appropriate cfDNA to perform the analyses was obtained in 18/20 cases. The sensitivity of cfDNA to detect the mutations present in paired FFPE samples was 69% (95% CI: 60–78%). The mutational landscape found in cfDNA samples was highly consistent with that of the tissue, with the most frequently mutated genes being B2M (61%), SOCS1 (61%), GNA13 (44%), STAT6 (44%), NFKBIA (39%), ITPKB (33%), and NFKBIE (33%). Overall, we observed a 75% concordance to detect CNA gains/losses between DNA microarray and low-pass WGS. The sensitivity of low-pass WGS was remarkably higher for clonal CNA (18/20, 90%) compared to subclonal alterations identified by DNA microarray. No significant associations between cfDNA amount and tumor burden or outcome were found. cfDNA is an excellent alternative source for the accurate genetic characterization of PMBL cases.

Association of PTPRT mutations with immune checkpoint inhibitors response and outcome in melanoma and non-small cell lung cancer

Purpose

Protein tyrosine phosphatase receptor type T (PTPRT), which is a well‐known phosphatase and mutates frequently in melanoma and non‐small cell lung cancer (NSCLC). Our research aims to elucidate its mutation association with immune checkpoint inhibitors (ICI) efficacy.

Methods

We integrated whole‐exome sequencing (WES)‐based somatic mutation profiles and clinical characteristics of 631 melanoma samples received ICI agents from eight studies and 109 NSCLC samples from two studies. For validation, 321 melanoma and 350 NSCLC immunotherapy samples with targeted next‐generation sequencing (NGS) were employed. Besides, an independent NSCLC cohort contained 240 samples was also collected for further corroboration. Distinct immune infiltration was evaluated according to the PTPRT mutational status.

Results

In the WES melanoma cohort, patients with PTPRT mutations harbored a significantly elevated ICI response rate (40.5% vs. 28.6%, p = 0.036) and a prolonged survival outcome (35.3 vs. 24.9 months, p = 0.006). In the WES NSCLC cohort, the favorable response and immunotherapy survival were also observed in PTPRT‐mutated patients (p = 0.036 and 0.019, respectively). For the validation cohorts, the associations of PTRPT mutations with better prognoses were identified in melanoma, NSCLC, and pan‐cancer patients with targeted‐NGS (all p < 0.05). Moreover, immunology analyses showed the higher mutation burden, increased lymphocyte infiltration, decreased‐ activated‐stroma, and immune response pathways were detected in patients with PTPRT mutations.

Conclusion

Our investigation indicates that PTPRT mutations may be considered as a potential indicator for assessing ICI efficacy in melanoma and NSCLC, even across multiple cancers. Further prospective validation cohorts are warranted.

Predictive Value of Max's Giant Associated Protein Mutation in Outcomes of Lung Adenocarcinoma Patients Treated With Immune Checkpoint Inhibitors

Treatment with immune checkpoint inhibitors (ICIs) has considerably improved prognosis in multiple cancers. However, regardless of PD-L1 expression and TMB, better predictive biomarkers are required to identify ICI-responsive patients. We analyzed a pan-cancer cohort as the discovery cohort to identify the role of Max’s giant associated protein (MGA) mutation in the outcome of ICI treatment in different types of cancers. A pooled lung adenocarcinoma (LUAD) cohort was considered as the validation cohort. Another two LUAD cohorts who received conventional treatment were included for prognostic analysis and mechanism exploration. In the discovery cohort, MGA mutation was a favorable survival biomarker for patients with LUAD than in those with other types of cancers. MGA mutation was positively correlated with the TMB score. The results of the validation cohort were consistent with those of the discovery cohort. Patients with MGA mutation in the TMB-low subgroup had longer survival. Two LUAD cohorts who received standard treatment showed that the MGA mutation was not a prognostic biomarker for standard treatment. Mechanically, we found that the co-mutant genes did not affect the prognostic role of MGA mutation. Gene-set enrichment analysis revealed that genes belonging to the immunodeficiency pathway were enriched in the MGA wild-type group in LUAD. Moreover, activated NK cells were more enriched in the MGA mutant LUAD group. In conclusion, our results demonstrated that MGA mutation was an independent predictive biomarker for ICI therapy. These results may provide a novel insight into identifying potential patients with LUAD for ICI therapy.