TP53 Mutation Infers a Poor Prognosis and Is Correlated to Immunocytes Infiltration in Breast Cancer

Efficacy and Safety of Immune Checkpoint Blockade in Patients With Li-Fraumeni Syndrome

A case series evaluating efficacy and safety of immune checkpoint blockade in Li-Fraumeni syndrome.

Tumor microenvironmental determinants of high-risk DCIS progression

Ductal carcinoma in situ (DCIS) constitutes an array of morphologically recognized intraductal neoplasms in the mammary ductal tree defined by an increased risk for subsequent invasive carcinomas at or near the site of biopsy detection. However, only 15-45% of untreated DCIS cases progress to invasive cancer, so understanding mechanisms that prevent progression is key to avoid overtreatment and provides a basis for alternative therapies and prevention. This study was designed to characterize the tumor microenvironment and molecular profile of high-risk DCIS that grew to a large size but remained as DCIS. All patients had DCIS lesions >5cm in size with at least one additional high-risk feature: young age (<45 years), high nuclear grade, hormone receptor negativity, HER2 positivity, the presence of comedonecrosis, or a palpable mass. The tumor immune microenvironment was characterized using multiplex immunofluorescence to identify immune cells and their spatial relationships within the ducts and stroma. Gene copy number analysis and whole exome DNA sequencing identified the mutational burden and driver mutations, and quantitative whole-transcriptome/gene expression analyses were performed. There was no association between the percent of the DCIS genome characterized by copy number variants (CNAs) and recurrence events (DCIS or invasive). Mutations, especially missense mutations, in the breast cancer driver genes PIK3CA and TP53 were common in this high-risk DCIS cohort (47% of evaluated lesions). Tumor infiltrating lymphocyte (TIL) density was higher in DCIS lesions with TP53 mutations (p=0.0079) compared to wildtype lesions, but not in lesions with PIK3CA mutations (p=0.44). Immune infiltrates were negatively associated with hormone receptor status and positively associated with HER2 expression. High levels of CD3+CD8- T cells were associated with good outcomes with respect to any subsequent recurrence (DCIS or invasive cancer), whereas high levels of CD3+Foxp3+ Treg cells were associated with poor outcomes. Spatial proximity analyses of immune cells and tumor cells demonstrated that close proximity of T cells with tumor cells was associated with good outcomes with respect to any recurrence as well as invasive recurrences. Interestingly, we found that myoepithelial continuity (distance between myoepithelial cells surrounding the involved ducts) was significantly lower in DCIS lesions compared to normal tissue (p=0.0002) or to atypical ductal hyperplasia (p=0.011). Gene set enrichment analysis identified several immune pathways associated with low myoepithelial continuity and a low myoepithelial continuity score was associated with better outcomes, suggesting that gaps in the myoepithelial layer may allow access/interactions between immune infiltrates and tumor cells. Our study demonstrates the immune microenvironment of DCIS, in particular the spatial proximity of tumor cells and T cells, and myoepithelial continuity are important determinants for progression of disease.

Cell fate regulation governed by p53: Friends or reversible foes in cancer therapy

Cancer is a leading cause of death worldwide. Targeted therapies aimed at key oncogenic driver mutations in combination with chemotherapy and radiotherapy as well as immunotherapy have benefited cancer patients considerably. Tumor protein p53 (TP53), a crucial tumor suppressor gene encoding p53, regulates numerous downstream genes and cellular phenotypes in response to various stressors. The affected genes are involved in diverse processes, including cell cycle arrest, DNA repair, cellular senescence, metabolic homeostasis, apoptosis, and autophagy. However, accumulating recent studies have continued to reveal novel and unexpected functions of p53 in governing the fate of tumors, for example, functions in ferroptosis, immunity, the tumor microenvironment and microbiome metabolism. Among the possibilities, the evolutionary plasticity of p53 is the most controversial, partially due to the dizzying array of biological functions that have been attributed to different regulatory mechanisms of p53 signaling. Nearly 40 years after its discovery, this key tumor suppressor remains somewhat enigmatic. The intricate and diverse functions of p53 in regulating cell fate during cancer treatment are only the tip of the iceberg with respect to its equally complicated structural biology, which has been painstakingly revealed. Additionally, TP53 mutation is one of the most significant genetic alterations in cancer, contributing to rapid cancer cell growth and tumor progression. Here, we summarized recent advances that implicate altered p53 in modulating the response to various cancer therapies, including chemotherapy, radiotherapy, and immunotherapy. Furthermore, we also discussed potential strategies for targeting p53 as a therapeutic option for cancer.

Lactylation-related gene signature for prognostic prediction and immune infiltration analysis in breast cancer

Background

Lactylation is implicated in various aspects of tumor biology, but its relation to breast cancer remains poorly understood. This study aimed to explore the roles of the lactylation-related genes in breast cancer and its association with the tumor microenvironment.

Methods

The expression and mutation patterns of lactylation-related genes were analyzed using the breast cancer data from The Cancer Genome Atlas (TCGA) database and GSE20685 datasets. Unsupervised clustering was used to identify two lactylation clusters. A lactylation-related gene signature was developed and validated using the training and validation cohorts. Immune cell infiltration and drug response were assessed.

Results

We analyzed the mRNA expression, copy number variations, somatic mutations, and correlation networks of 22 lactylation-related genes in breast cancer tissues. We identified two distinct lactylation clusters with different survival outcomes and immune microenvironments. We further classified the patients into two gene subtypes based on lactylation clusters and identified a 7-gene signature for breast cancer survival prognosis. The prognostic score based on this signature demonstrated prognostic value and predicted the therapeutic response.

Conclusion

Lactylation-related genes play a critical role in breast cancer by influencing tumor growth, immune microenvironment, and drug response. This lactylation-related gene signature may serve as a prognostic marker and a potential therapeutic target for breast cancer.

Construction and validation of a colon cancer prognostic model based on tumor mutation burden-related genes

Currently, immunotherapy has entered the clinical diagnosis and treatment guidelines for colon cancer, but existing immunotherapy markers cannot predict the effectiveness of immunotherapy well. This study utilized the TCGA-COAD queue to perform differential gene analysis on high and low-mutation burden samples, and screen differentially expressed genes (DEGs). To explore new molecular markers or predictive models of immunotherapy by using DEGs for NMF classification and prognostic model construction. Through systematic bioinformatics analysis, the TCGA-COAD cohort was successfully divided into high mutation burden subtypes and low mutation burden subtypes by NMF typing using DEGs. The proportion of MSI-H between high mutation burden subtypes was significantly higher than that of low mutation burden subtypes, but there was no significant difference in immunotherapy efficacy between the two subtypes. Drug sensitivity analysis showed significant differences in drug sensitivity between the two subtypes. Subsequently, we constructed a prognostic model using DEGs, which can effectively predict patient survival and immunotherapy outcomes. The prognosis and immunotherapy outcomes of the low-risk group were significantly better than those of the high-risk group. The external dataset validation of the constructed prognostic model using the GSE39582 dataset from the GEO database yielded consistent results. At the same time, we also analyzed the TMB and MSI situation between the high and low-risk groups, and the results showed that there was no significant difference in TMB between the high and low-risk groups, but the proportion of MSI-H in the high-risk group was significantly higher than that in the low-risk group. Finally, we conclude that TMB is not a suitable molecular marker for predicting the efficacy of immunotherapy in colon cancer. The newly constructed prognostic model can effectively differentiate the prognosis of colon cancer patients and predict their immunotherapy efficacy.

The heterogeneous impact of targeted therapy on the prognosis of stage III/IV colorectal cancer patients with different subtypes of TP53 mutations

BACKGROUND

The relationship between molecular characteristics and the prognosis of colorectal cancer (CRC) patients has not been fully understood. This study explored the impact of targeted therapy on the prognosis of CRC patients with different TP53 mutations, in the context of comprehensive treatment.

METHODS

This study included patients with stage III/IV primary CRC from the electronic medical record system. TP53 mutations were detected via next-generation sequencing (NGS) using formalin-fixed paraffin-embedded (FFPE) tissues. Applying two methods, we classified TP53 mutations as gain of function (GOF)/non-GOF mutations or known/likely loss of function (LOF) mutations. Kaplan-Meier plot and parametric survival analysis were performed to evaluate the prognosis of CRC patients and identify potential predictors.

RESULTS

There were 286 patients included, of which 166 (58.04%) patients received targeted therapy and 120 (41.96%) did not. There were 286 patients in the TP53 GOF classification set and 247 in the TP53 LOF classification set. Parametric survival analysis, adjusted for sex, onset, KRAS mutation, sidedness, stage, and surgery, showed that receiving targeted therapy predicted better overall survival (OS) among patients who harbored TP53 GOF mutations (HR 0.40, 95% confidence interval (CI) [0.21, 0.76], p = 0.005) or known LOF mutations (HR 0.21, 95% CI [0.07, 0.60], p = 0.002). However, there was no significant impact of receiving targeted therapy on OS among patients harboring TP53 non-GOF mutations (HR 1.68, 95% CI [0.50, 5.63], p = 0.403) or likely LOF mutations (HR 0.90, 95% CI [0.34, 2.39], p = 0.837).

CONCLUSIONS

Receiving targeted therapy had a heterogeneous impact on the prognosis of CRC patients harboring different TP53 mutations. These results provide promising value for future personalized treatment and precision medicine.

Neratinib + fulvestrant + trastuzumab for HR-positive, HER2-negative, HER2-mutant metastatic breast cancer: outcomes and biomarker analysis from the SUMMIT trial

BACKGROUND

HER2 mutations are targetable alterations in patients with hormone receptor-positive (HR+) metastatic breast cancer (MBC). In the SUMMIT basket study, patients with HER2-mutant MBC received neratinib monotherapy, neratinib + fulvestrant, or neratinib + fulvestrant + trastuzumab (N + F + T). We report results from 71 patients with HR+, HER2-mutant MBC, including 21 (seven in each arm) from a randomized substudy of fulvestrant versus fulvestrant + trastuzumab (F + T) versus N + F + T.

PATIENTS AND METHODS

Patients with HR+ HER2-negative MBC with activating HER2 mutation(s) and prior cyclin-dependent kinase 4/6 inhibitor (CDK4/6i) therapy received N + F + T (oral neratinib 240 mg/day with loperamide prophylaxis, intramuscular fulvestrant 500 mg on days 1, 15, and 29 of cycle 1 then q4w, intravenous trastuzumab 8 mg/kg then 6 mg/kg q3w) or F + T or fulvestrant alone. Those whose disease progressed on F + T or fulvestrant could cross-over to N + F + T. Efficacy endpoints included investigator-assessed objective response rate (ORR), clinical benefit rate (RECIST v1.1), duration of response, and progression-free survival (PFS). Plasma and/or formalin-fixed paraffin-embedded tissue samples were collected at baseline; plasma was collected during and at end of treatment. Extracted DNA was analyzed by next-generation sequencing.

RESULTS

ORR for 57 N + F + T-treated patients was 39% [95% confidence interval (CI) 26% to 52%); median PFS was 8.3 months (95% CI 6.0-15.1 months). No responses occurred in fulvestrant- or F + T-treated patients; responses in patients crossing over to N + F + T supported the requirement for neratinib in the triplet. Responses were observed in patients with ductal and lobular histology, 1 or ≥1 HER2 mutations, and co-occurring HER3 mutations. Longitudinal circulating tumor DNA sequencing revealed acquisition of additional HER2 alterations, and mutations in genes including PIK3CA, enabling further precision targeting and possible re-response.

CONCLUSIONS

The benefit of N + F + T for HR+ HER2-mutant MBC after progression on CDK4/6is is clinically meaningful and, based on this study, N + F + T has been included in the National Comprehensive Cancer Network treatment guidelines. SUMMIT has improved our understanding of the translational implications of targeting HER2 mutations with neratinib-based therapy.

Decoding tumor heterogeneity in uveal melanoma: basement membrane genes as novel biomarkers and therapeutic targets revealed by multi-omics approaches for cancer immunotherapy

Background: Uveal melanoma (UVM) is a primary intraocular malignancy that poses a significant threat to patients' visual function and life. The basement membrane (BM) is critical for establishing and maintaining cell polarity, adult function, embryonic and organ morphogenesis, and many other biological processes. Some basement membrane protein genes have been proven to be prognostic biomarkers for various cancers. This research aimed to develop a novel risk assessment system based on BMRGs that would serve as a theoretical foundation for tailored and accurate treatment. Methods: We used gene expression profiles and clinical data from the TCGA-UVM cohort of 80 UVM patients as a training set. 56 UVM patients from the combined cohort of GSE84976 and GSE22138 were employed as an external validation dataset. Prognostic characteristics of basement membrane protein-related genes (BMRGs) were characterized by Lasso, stepwise multifactorial Cox. Multivariate analysis revealed BMRGs to be independent predictors of UVM. The TISCH database probes the crosstalk of BMEGs in the tumor microenvironment at the single-cell level. Finally, we investigated the function of ITGA5 in UVM using multiple experimental techniques, including CCK8, transwell, wound healing assay, and colony formation assay. Results: There are three genes in the prognostic risk model (ADAMTS10, ADAMTS14, and ITGA5). After validation, we determined that the model is quite reliable and accurately forecasts the prognosis of UVM patients. Immunotherapy is more likely to be beneficial for UVM patients in the high-risk group, whereas the survival advantage may be greater for UVM patients in the low-risk group. Knockdown of ITGA5 expression was shown to inhibit the proliferation, migration, and invasive ability of UVM cells in vitro experiments. Conclusion: The 3-BMRGs feature model we constructed has excellent predictive performance which plays a key role in the prognosis, informing the individualized treatment of UVM patients. It also provides a new perspective for assessing pre-immune efficacy.

Screening and Verification of Key Ubiquitination Genes Related to Immune Infiltration in Stage III/IV Hepatocellular Carcinoma

Introduction

Immune checkpoint therapy (ICIs) effectively improves the prognosis of advanced (stage III/IV) hepatocellular carcinoma (HCC) patients. However, its objective response rate (ORR) is below 20%, significantly limiting ICI use in advanced HCC patients. The level of tumour immune infiltration influences ICI response rate. Recent studies have found ubiquitinase to be an important factor that regulates tumour immune infiltration. Therefore, the aim of this study is to explore the key ubiquitination genes that regulate immune infiltration in advanced HCC and further validate them.

Methods

A biotechnological process was performed as a means of classifying 90 advanced HCC patients into three immune subtypes and identifying associations with immune infiltration in the co-expressed modules. Ubiquitination-related genes were then screened with WGCNA. Gene enrichment analysis was performed for the target module and 30 hub genes were screened out by protein-protein interaction network (PPI). ssGSEA, single-gene sequencing and the MCP counter were used for exploring immune infiltration. TIDE score was applied for predicting drug efficacy and GSEA was used for exploring potential pathways. Finally, GRB2 expression in HCC tissue was validated by in vitro experiments.

Results

GRB2 expression was found to have a significant correlation with the pathological stage and prognosis of HCC patients and a positive correlation with immune infiltration and tumour mutation burden (TMB). In addition, significant correlations with the efficacy of ICIs, sorafenib and transarterial chemoembolization (TACE) were identified. GRB2 was found to be most significantly associated with the JAK-STAT signalling pathway and cytosolic DNA sensing pathway. Finally, it was found that GRB2 expression is closely related to the prognosis, tumour size and TMN stage.

Conclusion

A significant association was observed between the ubiquitinated gene GRB2 and the prognosis and immune infiltration of advanced HCC patients and it may potentially be used for predicting therapy efficacy in advanced HCC patients in the future.

Peripheral immune cell profiling of double-hit lymphoma by mass cytometry

BACKGROUND

Double-hit or Triple-hit lymphoma (DHL/THL) is a subset of high-grade B cell lymphoma harboring rearrangements of MYC and BCL2 and/or BCL6, and usually associate with aggressive profile, while current therapies tend to provide poor clinical outcomes and eventually relapsed. Further explorations of DHL at cellular and molecular levels are in demand to offer guidance for clinical activity.

METHODS

We collected the peripheral blood of DHL patients and diffused large B cell lymphoma (DLBCL) patients from single institute and converted them into PBMC samples. Mass cytometry was then performed to characterize these samples by 42 antibody markers with samples of healthy people as control. We divided the immune cell subtypes based on the expression profile of surface antigens, and the proportion of each cell subtype was also analyzed. By comparing the data of the DLBCL group and the healthy group, we figured out the distinguished immune cell subtypes of DHL patients according to their abundance and marker expression level. We further analyzed the heterogeneity of DHL samples by pairwise comparison based on clinical characteristics.

RESULTS

We found double-positive T cells (DPT) cells were in a significantly high percentage in DHL patients, whereas the ratio of double-negative T cells (DNT) was largely reduced in patients. Besides, CD38 was uniquely expressed at a high level on some naïve B cells of DHL patients, which could be a marker for the diagnosis of DHL (distinguishing from DLBCL), or even be a drug target for the treatment of DHL. In addition, we illustrated the heterogeneity of DHL patients in terms of immune cell landscape, and highlighted TP53 as a major factor that contributes to the heterogeneity of the T cells profile.

CONCLUSION

Our study demonstrated the distinct peripheral immune cell profile of DHL patients by contrast to DLBCL patients and healthy people, as well as the heterogeneity within the DHL group, which could provide valuable guidance for the diagnosis and treatment of DHL.

Construction and characterization of a cuproptosis- and immune checkpoint-based LncRNAs signature for breast cancer risk stratification

BACKGROUND

Cuproptosis is the most recently identified form of cell death, and copper homeostasis is an important cancer therapeutic target. However, the therapeutic benefits of cuproptosis-targeted treatment in BRCA remain undetermined. This study utilized LncRNAs linked to cuproptosis genes and immune checkpoint genes to generate a BRCA predictive signature.

METHODS

We screened a population of LncRNAs that correlated with both cuproptosis genes and immune checkpoint genes and used ten of these LncRNAs to construct a prognosis-predictive signature. We then validated and proved the efficacy of the signature in predicting the prognosis of BRCA patients. We also unraveled the relationship between the signature and the immunological milieu, immune function, and susceptibility to chemotherapy.

RESULTS

The signature derived from the ten cuproptosis- and immune-related prognostic LncRNAs (CuImP-LncRNAs) can be implied to categorize patients into two groups, including the high- and low-risk groups. The value of the signature was validated, and the risk score was verified as an independent prognostic indicator. The TIME and TMB distribution patterns and chemosensitivity were depicted in the high- and low-risk groups, respectively. Patients of the high-risk group with a suppressive immunological intratumor context were more sensitive to a broad range of antitumor agents. In contrast, low-risk individuals with active immune function responded more favorably to immunotherapy.

CONCLUSION

Our findings provided a novel and effective model for predicting BRCA prognosis and the propensity to different treatment modalities, thus contributing to the optimization of personalized BRCA therapy in the future.

Molecular Classification, Treatment, and Genetic Biomarkers in Triple-Negative Breast Cancer: A Review

Breast cancer is the most common malignancy and the second most common cause of cancer-related mortality in women. Triple-negative breast cancers do not express estrogen receptors, progesterone receptors, or human epidermal growth factor receptor 2 and have a higher recurrence rate, greater metastatic potential, and lower overall survival rate than those of other breast cancers. Treatment of triple-negative breast cancer is challenging; molecular-targeted therapies are largely ineffective and there is no standard treatment. In this review, we evaluate current attempts to classify triple-negative breast cancers based on their molecular features. We also describe promising treatment methods with different advantages and discuss genetic biomarkers and other prediction tools. Accurate molecular classification of triple-negative breast cancers is critical for patient risk categorization, treatment decisions, and surveillance. This review offers new ideas for more effective treatment of triple-negative breast cancer and identifies novel targets for drug development.

Analysis of Tumor Microenvironment Heterogeneity among Breast Cancer Subtypes to Identify Subtype-Specific Signatures

Breast cancer is one of the most frequent malignancies in women worldwide. According to 50-gene signature, Prediction Analysis of Microarray 50 (PAM50), breast cancer can be categorized into five molecular subtypes, and these subtypes are highly heterogeneous in different molecular characteristics. However, the landscape of their tumor microenvironment (TME) heterogeneity has not been fully researched. Using the multi-omics dataset of breast cancer from the METABRIC cohort (n = 1699), we conducted extensive analyses of TME-related features to investigate TME heterogeneity in each breast cancer subtype. We then developed a cell-based subtype set enrichment analysis to identify the subtype-specific TME cells, and further evaluate their prognostic effects. Our results illustrate that different breast cancer subtypes exhibit different TME patterns. Basal-like and HER2-enriched subtypes are associated with high immune scores, expression of most immune regulatory targets, and immune cell infiltration, suggesting that these subtypes could be defined as "immune hot" tumors and suitable for immune checkpoint blockade (ICB) therapy. In contrast, Luminal A and Luminal B subtypes are associated with low immune scores and immune cell infiltration, suggesting that these subtypes could be defined as "immune cold" tumors. Additionally, the Normal-like subtype has relatively high levels of both immune and stromal features, which indicates that the Normal-like subtype may be suitable for more diverse treatment strategies. Our study reveals the breast cancer tumor microenvironment heterogeneity across subtypes. The comprehensive analysis of breast cancer TME-related characteristics may help us to adopt a tailored treatment strategy for different subtypes of patients.

Identification of a glycolysis- and lactate-related gene signature for predicting prognosis, immune microenvironment, and drug candidates in colon adenocarcinoma

Background: Colon adenocarcinoma (COAD), a malignant gastrointestinal tumor, has the characteristics of high mortality and poor prognosis. Even in the presence of oxygen, the Warburg effect, a major metabolic hallmark of almost all cancer cells, is characterized by increased glycolysis and lactate fermentation, which supports biosynthesis and provides energy to sustain tumor cell growth and proliferation. However, a thorough investigation into glycolysis- and lactate-related genes and their association with COAD prognosis, immune cell infiltration, and drug candidates is currently lacking.

Methods: COAD patient data and glycolysis- and lactate-related genes were retrieved from The Cancer Genome Atlas (TCGA) and Gene Set Enrichment Analysis (GSEA) databases, respectively. After univariate Cox regression analysis, a nonnegative matrix factorization (NMF) algorithm was used to identify glycolysis- and lactate-related molecular subtypes. Least absolute shrinkage and selection operator (LASSO) Cox regression identified twelve glycolysis- and lactate-related genes (ADTRP, ALDOB, APOBEC1, ASCL2, CEACAM7, CLCA1, CTXN1, FLNA, NAT2, OLFM4, PTPRU, and SNCG) related to prognosis. The median risk score was employed to separate patients into high- and low-risk groups. The prognostic efficacy of the glycolysis- and lactate-related gene signature was assessed using Kaplan–Meier (KM) survival and receiver operating characteristic (ROC) curve analyses. The nomogram, calibration curves, decision curve analysis (DCA), and clinical impact curve (CIC) were employed to improve the clinical applicability of the prognostic signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on differentially expressed genes (DEGs) from the high- and low-risk groups. Using CIBERSORT, ESTIMATE, and single-sample GSEA (ssGSEA) algorithms, the quantities and types of tumor-infiltrating immune cells were assessed. The tumor mutational burden (TMB) and cytolytic (CYT) activity scores were calculated between the high- and low-risk groups. Potential small-molecule agents were identified using the Connectivity Map (cMap) database and validated by molecular docking. To verify key core gene expression levels, quantitative real-time polymerase chain reaction (qRT–PCR) assays were conducted.

Results: We identified four distinct molecular subtypes of COAD. Cluster 2 had the best prognosis, and clusters 1 and 3 had poor prognoses. High-risk COAD patients exhibited considerably poorer overall survival (OS) than low-risk COAD patients. The nomogram precisely predicted patient OS, with acceptable discrimination and excellent calibration. GO and KEGG pathway enrichment analyses of DEGs revealed enrichment mainly in the “glycosaminoglycan binding,” “extracellular matrix,” “pancreatic secretion,” and “focal adhesion” pathways. Patients in the low-risk group exhibited a larger infiltration of memory CD4+ T cells and dendritic cells and a better prognosis than those in the high-risk group. The chemotherapeutic agent sensitivity of patients categorized by risk score varied significantly. We predicted six potential small-molecule agents binding to the core target of the glycolysis- and lactate-related gene signature. ALDOB and APOBEC1 mRNA expression was increased in COAD tissues, whereas CLCA1 and OLFM4 mRNA expression was increased in normal tissues.

Conclusion: In summary, we identified molecular subtypes of COAD and developed a glycolysis- and lactate-related gene signature with significant prognostic value, which benefits COAD patients by informing more precise and effective treatment decisions.

Disease-related thrombocytopenia in myelofibrosis is defined by distinct genetic etiologies and is associated with unique prognostic correlates

BACKGROUND

Thrombocytopenia in patients with myelofibrosis (MF) is prognostically detrimental and poses a therapeutic challenge. MF patients with thrombocytopenia are considered high-risk by most prognostic models and their distinct phenotype has given rise to the emerging concept of cytopenic MF. Yet, the mechanisms underlying thrombocytopenia in MF are poorly understood.

METHODS

This study aimed to highlight the genetic mechanisms driving low platelet counts in treatment-naive MF patients, establish their phenotypic correlates, and assess prognostic factors specific to this group of patients.

RESULTS

The authors found that most patients presenting with low platelets had a clear thrombocytopenia-specific genetic abnormality involving a U2AF1 Q157 mutation, deletion 20q, molecular complexity (three or more mutations), or high-risk karyotype. Etiologic clustering did not correlate with prognosis; however, thrombocytopenic patients were found to have unique prognostic variables including low serum albumin and mutations of SRSF2 and TP53. This led to the proposal of a prognostic model (SRSF2, albumin, TP53 score) that stratifies thrombocytopenic patients as low, intermediate, or high-risk with corresponding median survivals of 93.5, 29.5, and 7.2 months, respectively.

CONCLUSIONS

This study demonstrates that thrombocytopenia in MF is driven by different genetic mechanisms and is not uniformly high-risk. As novel agents with improved hematologic safety profiles enter the treatment landscape, thoughtful, risk-adapted therapeutic decisions will be required for MF patients with thrombocytopenia.

LAY SUMMARY

A significant minority of patients with myelofibrosis (MF) present with low platelets. Historically, these patients have been viewed as having "high-risk" disease, but this may not be uniformly true. Our study shows that there are various different causes for low platelets in MF, some of which represent high-risk disease whereas others do not. Additionally, our study shows that genetic mutations affecting the genes SRSF2 and TP53 are uniquely problematic in this group, as is a low serum albumin level. This study helps to risk-stratify MF patients with thrombocytopenia, thereby providing more information to guide informed and individualized treatment decisions.

An immune-related gene prognostic risk index for pancreatic adenocarcinoma

Objective

Our goal is to construct an immune-related gene prognostic risk index (IRGPRI) for pancreatic adenocarcinoma (PAAD), and to clarify the immune and molecular features in IRGPRI-defined PAAD subgroups and the benefit of immune checkpoint inhibitors (ICIs) therapy.

Method

Through differential gene expression analysis, weighted gene co-expression network analysis (WGCNA), and univariate Cox regression analysis, 16 immune-related hub genes were identified using the Cancer Genome Atlas (TCGA) PAAD dataset (n = 182) and immune gene set. From these genes, we constructed an IRGPRI with the Cox regression method and the IRGPRI was verified based on the Gene Expression Omnibus (GEO) dataset (n = 45). Then, we analyzed the immune and molecular features and the benefit of ICI therapy in IRGPRI-defined subgroups.

Results

Five genes, including S100A16, CD40, VCAM1, TNFRSF4 and TRAF1 were used to construct IRGPRI. As with the results of the GEO cohort, the overall survival (OS) was more favorable in low IRGPRI patients versus high IRGPRI patients. The composite results pointed out that low IRGPRI was associated with immune response-related pathways, high level of CTLA4, low KRAS and TP53 mutation rate, more infiltration of activated memory CD4⁺ T cells, CD8⁺ T cells, and more benefits from ICIs therapy. In comparison, high IRGPRI was associated with cancer-related pathways, low expression of CTLA4, high KRAS and TP53 mutation rate, more infiltration of M2 macrophages, and less benefit from ICIs therapies.

Conclusion

This IRGPRI is an encouraging biomarker to define the prognosis, immune and molecular features, and benefits from ICIs treatments in PAAD.

Receptor–ligand pair typing and prognostic risk model for papillary thyroid carcinoma based on single-cell sequencing

The papillary thyroid carcinoma (PTC) microenvironment consists of various cancer and surrounding cells, and the communication between them is mainly performed through ligand–receptor (LR) interactions. Single-cell RNA sequencing (scRNA-seq) has been performed to investigate the role of intercellular communication networks in tumor progression. In addition, scRNA-seq can accurately identify the characteristics of immune cell subsets, which is of great significance for predicting the efficacy of immunotherapy. In this study, the cell–cell communication network was analyzed through LR pairs, and a new PTC molecular phenotype was developed based on LR pairs. Furthermore, a risk model was established to predict patient response to PD-1 blockade immunotherapy. The scRNA-seq dataset was obtained from GSE184362, and the bulk tumor RNA-seq dataset was obtained from The Cancer Genome Atlas. CellPhoneDB was used for cellular communication analysis. LR pair correlations were calculated and used to identify molecular subtypes, and the least absolute shrinkage and selection operator (Lasso) Cox regression was used to develop a risk model based on LR pairs. The IMvigor210 and GSE78220 cohorts were used as external validations for the LR.score to predict responses to PD-L1 blockade therapy. A total of 149 LR pairs with significant expression and prognostic correlation were included, and three PTC molecular subtypes were obtained from those with significant prognostic differences. Then, five LR pairs were selected to construct the risk scoring model, a reliable and independent prognostic factor in the training set, test set, and whole dataset. Furthermore, two external validation sets confirmed the predictive efficacy of the LR.score for response to PD-1 blockade therapy.

Identification of Novel Characteristics in TP53-Mutant Hepatocellular Carcinoma Using Bioinformatics

Background: TP53 mutations are the most frequent mutations in hepatocellular carcinoma (HCC) and affect the occurrence and development of this cancer type. Therefore, it is essential to clarify the function and mechanism of TP53 mutations in HCC.

Methods: We performed a sequence of bioinformatic analyses to elucidate the characteristics of TP53 mutations in HCC. We downloaded the data of hepatocellular carcinoma from The Cancer Genome Atlas database and used different R packages for serial analyses, including gene mutation analysis, copy number variation analysis, analysis of the tumor mutational burden and microsatellite instability, differential gene expression analysis, and functional enrichment analysis of TP53 mutations, and performed gene set enrichment analysis. We established a protein-protein interaction network using the STRING online database and used the Cytoscape software for network visualization, and hub gene screening. In addition, we performed anticancer drug sensitivity analysis using data from the Genomics of Drug Sensitivity in Cancer. Immune infiltration and prognosis analyses were also performed.

Results: Missense mutations accounted for a great proportion of HCC mutations, the frequency of single nucleotide polymorphisms was high, and C > T was the most common form of single nucleotide variations. TP53 had a mutation rate of 30% and was the most commonly mutated gene in HCC. In the TP53 mutant group, the tumor mutational burden (p < 0.001), drug sensitivity (p < 0.05), ESTIMATE score (p = 0.038), and stromal score (p < 0.001) dramatically decreased. The Cytoscape software screened ten hub genes, including CT45A1, XAGE1B, CT55, GAGE2A, PASD1, MAGEA4, CTAG2, MAGEA10, MAGEC1, and SAGE1. The prognostic model showed a poor prognosis in the TP53 mutation group compared with that in the wild-type group (overall survival, p = 0.023). Univariate and multivariate cox regression analyses revealed that TP53 mutation was an independent risk factor for the prognosis of HCC patients (p <0.05). The constructed prognostic model had a favorable forecast value for the prognosis of HCC patients at 1 and 3 years (1-year AUC = 0.752, 3-years AUC = 0.702).

Conclusion: This study further deepened our understanding of TP53-mutated HCC, provided new insights into a precise individualized therapy for HCC, and has particular significance for prognosis prediction.

TP53 Co-Mutations in Advanced EGFR-Mutated Non-Small Cell Lung Cancer: Prognosis and Therapeutic Strategy for Cancer Therapy

Lung cancer is the leading cause of cancer-related deaths worldwide. As the most prevalent molecular mutation subtypes in non-small cell lung cancer (NSCLC), EGFR-TKIs are currently a standard first-line therapy for targeting the mutated EGFR in advanced NSCLC patients. However, 20-30% of this subset of patients shows primary resistance to EGFR-TKIs. Patients with co-mutations of EGFR and several other genes have a poor response to EGFR-TKIs, whereas the prognostic and predictive significance of EGFR/TP53 co-mutation in NSCLC patients remains controversial. Meanwhile, little is known about how to choose an optimal therapeutic strategy for this subset of patients. Presently, no drugs targeting TP53 mutations are available on the market, and some p53 protein activators are in the early stage of clinical trials. A combination of EGFR-TKIs with antiangiogenic agents or chemotherapy or other agents might be a more appropriate strategy to tackle the problem. In this review, we describe the prognostic and predictive value of EGFR/TP53 co-mutation in NSCLC patients, investigate the mechanisms of this co-mutation affecting the response to EGFR-TKIs, and further explore optimal regimens effectively to prolong the survival time of the NSCLC patients harboring this co-mutation.