Predictive Molecular Biomarkers Research Articles

Genomic characterization and molecular predictive biomarkers for chemotherapy in patients with metastatic triple-negative breast cancer treated in a real-world setting.

We aimed to characterize genomic alterations with potential prognostic or predictive significance in patients with metastatic triple-negative breast cancer (mTNBC) treated with chemotherapy in a real-world setting. Next-generation sequencing with FoundationOne® CDx was conducted primarily on primary tumor tissue from 112 consecutive patients with mTNBC. Genomic alterations were subdivided into canonical oncogenic pathways and noted for their involvement in homologous recombination deficiency (HRD). Altered genes and pathways were correlated with overall survival (OS) and evaluated regarding their association with real-world progression-free survival (rwPFS) in patients treated with different chemotherapy agents. Occurrence of alterations were compared between patients with exceptional response and rapid progression to chemotherapy. After exclusion due to insufficient tumor tissue or clinical data, material from 97 patients was analyzed. The most frequently altered genes were TP53 (82 %), RAD21 (25 %) and PIK3CA (23 %). Altogether, 26 % of patients had an alteration leading to HRD. None of the analyzed alterations were associated with OS. Variants leading to HRD were associated with a prolonged rwPFS in patients treated with platinum-based chemotherapy in the first line setting (hazard ratio [HR], 0.31 [95% CI: 0.12-0.84]). Exceptional responders more often exhibited alterations in the MYC and RAS/RTK pathways compared to rapid progressors. Patients with tumor alterations in HRD-related genes seem to define subgroups that respond favorably to platinum-based chemotherapy. Further research into the genomic landscape of tumors from patients with rapid progression or exceptional response to different treatment strategies can provide insights into mechanisms of resistance and identify predictive biomarkers.

Identification of PANoptosis associated lncRNAs associated with clinical prognosis and immune infiltration microenvironment in colon adenocarcinoma

Early diagnosis and disease management based on risk stratification have a very positive impact on colon adenocarcinoma (COAD) prognosis. It is of positive significance to further explore risk stratification of COAD patients and identify predictive molecular biomarkers. PANoptosis is defined as a form of inflammatory cell death regulated by PANoptosome, with common features of pyroptosis, apoptosis and necroptosis. The role of PANoptosis in COAD has not been fully studied. In this study, we analyzed significant differences in the expression of PANoptosis-related gene (PRG) features in COAD. Subsequently, the PANoptosis associated lncRNAs (PALs) associated with PRGs were analyzed by LASSO algorithm and multivariate Cox analysis, and PALs related to the prognosis of COAD were selected. Based on the expression patterns of prognostic PAL features, we performed unsupervised consensus cluster analysis to categorize COAD samples into distinct PAL molecular subtypes and investigate their associated immune infiltration characteristics. We subsequently constructed PAL score model based on prognostic characteristics and verified its independent prognostic value for COAD. The nomogram diagnostic model was established to confirm the prognostic value of PAL scoring system again. Pathway enrichment analysis, somatic mutation profiling, and drug sensitivity analysis were employed to comprehensively assess the clinical value of the PAL score. Additionally, qRT-PCR was used to further validate the abnormal expression of the selected targets in COAD. Our results provide a new idea for clinical risk stratification and new evidence for the role of PANoptosis in COAD.

Predictive Molecular Biomarkers of Bladder Cancer Identified by Next-Generation Sequencing-Preliminary Data.

Background: The majority of patients with bladder cancer suffer from tumour recurrence. Identifying prognostic factors for tumour recurrence is crucial for treatment and follow-up in affected patients. The study aimed to assess the impact of somatic mutations in bladder cancer on patient outcomes and tumour recurrence. Methods: The study group comprised 46 patients with urothelial bladder cancers referred for transurethral resection of the tumour. A molecular study on tumour-derived DNA was performed using next-generation sequencing. Somatic mutations were screened in 50 genes involved in carcinogenesis. Results: We identified 81 variants in 23 genes, including 54 pathogenic mutations, 18 likely pathogenic variants, and 9 variants of unknown significance. The most frequently mutated genes were FGFR3, PIK3CA, and TP53 in 52%, 35%, and 24% of tumours, respectively. The average tumour-free survival was significantly longer in cases with mutations in the PIK3CA gene (p = 0.02), and mutations in the PIK3CA gene were associated with a decreased risk of tumour recurrence (Hazard Ratio = 0.26; 95% CI: 0.11-0.62; p = 0.018). Conclusions: The PIK3CA gene was shown to be a predictive marker of a low risk of bladder tumour recurrence. Molecular screening of bladder cancers supported predictive biomarkers of tumour recurrence and showed that tumour-free survival is molecularly determined.

Advances in the diagnosis of colorectal cancer: the application of molecular biomarkers and imaging techniques: a literature review

Background: Following neoplasms of the lung and breast, colorectal cancer (CRC) is the third most frequent malignancy globally. Screening for CRC at the age of 50 years is strongly encouraged for prompt earlier diagnosis owing to prognoses being greatly correlated with time of detection and cancer staging. Aim: This review aimed to elucidate the most recent advancements in the detection of CRC, with an emphasis on the latest innovations in diagnostic molecular biomarkers in conjunction with radiological imaging alongside stool-based tests for CRC screening. Methods: A comprehensive review of the literature was performed, focusing on specific terms in different electronic databases, including that of PubMed/MEDLINE. Keywords pertaining to “colorectal cancer,” “diagnosis,” “screening,” “imaging,” and “biomarkers,” among others, were employed in the search strategy. Articles screened and evaluated were deemed relevant to the study aim and were presented in the medium of the English language. Results: There have been several innovations in the diagnostics and identification of CRC. These generally comprise molecular biomarkers, currently being studied for suitability in disease detection. Examples of these include genetic, epigenetic, and protein biomarkers. Concurrently, recent developments in CRC diagnostics highlight the advancements made in radiological imaging that offer precise insights on tumor biology in addition to morphological information. Combining these with statistical methodologies will increase the sensitivity and specificity of CRC diagnostics. However, putting these strategies into reality is hampered by several issues. Conclusion: Progress in diagnostic technology alongside the identification of a few prognostic predictive molecular biomarkers suggested great promise for prompt detection and management of CRC. This clearly necessitates further efforts to learn more in this specific sector.

Epigenomic biomarkers of cardiometabolic disease: How far are we from daily practice?

Determining whether someone has cardiometabolic disease (CMD), especially in the early stages, can be complicated. Risk stratification ordinarily depends on an extended process relying on medical history that typically considers blood pressure, cholesterol, smoking and diabetes status. Physicians have long relied on these key patient characteristics to assess CMD risk. However, these widely used clinical assessments are often identified later in life and by definition, in those individuals with progressed disease. This is partly because the onset of CMD naturally occurs in adulthood, however, the underlying processes can occur much earlier in life, even in the absence of obvious symptoms. For one thing, the pathways towards pathology may exist for years before symptom onset. Thus, among other things, there are opportunities to provide doctors with better insights into future disease prediction especially in younger adults with diabetes. The rapid rise in CMD together with the increased rates of obesity and diabetes in this population only emphasises the importance of predictive molecular biomarkers. One notable aspect is that traditional risk scores, such as those based on cholesterol measurements, are frequently found to be within normal ranges in younger populations. At the same time, given the significant overlap in risk factors for cardiovascular disease (CVD) and diabetes, the unmet clinical need is for early biomarkers of CMD that may help improve risk assessment in younger adults. This editorial highlights advances in the use of polygenic risk scores and emerging utility of genetic biomarkers to define intermediate CMD phenotypes discussing new classification criteria involving DNA methylation of genes to improve risk assessment. CMD is the number one cause of mortality and accounts for 31% of all global deaths. CMD is also multifactorial, comprising cardiovascular disease (CVD) and diabetes that have significant overlap in risk factors and disease biology. Diabetes is arguably the strongest risk factor for CVD development. Accounting for almost 90% of diabetes cases worldwide, type 2 diabetes (T2D) affects about 527 million people. The global economic burden is estimated at 1.3 trillion USD annually and is close to 1.8% of global GDP [1]. Despite the progress in preventive and therapeutic measures of CVD, the increasing CMD rates only underscore the important need of molecular biomarkers for early detection [2]. Determining whether someone has CMD usually involves an extended diagnostic process that has become essential for risk stratification and disease prevention [3]. While the onset of CMD typically occurs in adulthood, disease development commences much earlier, and this has scientists questioning whether molecular biomarkers could improve current prognostic risk scores. Predicting which people with T2D are most likely to develop CVD remains a significant challenge despite the recent advances in genetic mapping.Graphical abstract

Molecular Subtypes Are Associated With Clinical Benefit in Cisplatin-Treated Metastatic Urothelial Cancer Patients.

Cisplatin-based combination chemotherapy (CHT) is standard of care in metastatic urothelial cancer (mUC); however, no predictive molecular biomarkers are available for clinical use. The aim of this study was to investigate the impact of molecular subtypes in relation to treatment response and survival in patients with mUC treated with first-line CHT. Molecular subtype classification according to the Lund Taxonomy (LundTax) was performed by tumor transcriptomic profiling and immunostaining in a retrospective cohort. Molecular subtypes were investigated in relation to the primary end point overall response rate (ORR) and secondary end points progression-free survival (PFS) and overall survival (OS). Differential gene expression and association to treatment response were explored. Ninety-five patients with mUC were classified into urothelial-like (Uro, 43%), genomically unstable (GU, 26%), basal squamous-like (Ba/Sq, 20%), mesenchymal-like (Mes-like, 8%), and small cell neuroendocrine-like (Sc/NE, 3%) subtypes. Patients with Mes-like tumors had lower ORR (14%) compared with Uro (70%), GU (77%), Ba/Sq (75%), and Sc/NE (67%; odds ratio, 0.06 [95% CI, 0.01 to 0.54], P = .012). Furthermore, patients with Mes-like tumors had significantly shorter PFS (hazard ratio [HR], 5.18 [95% CI, 2.28 to 11.76], P < .001) and OS (HR, 3.19 [95% CI, 1.45 to 7.03], P = .004). Patients with Uro and GU showed the longest survival. In responders, an enrichment of downregulated stromal- and immune-related genes was seen. Downregulation of interferon-induced transmembrane protein 2 was associated with increased ORR and improved OS. This study identifies different CHT responses by LundTax molecular subtypes in patients with mUC, where the Mes-like subtype was associated with lower response rate and shorter survival.

Analysis of Molecular Imaging and Laboratory Baseline Biomarkers in PSMA-RLT: Whole-Body Total Lesion PSMA (TLP) Predicts Overall Survival.

The aim of this retrospective study was to identify pre-therapeutic predictive laboratory and molecular imaging biomarkers for response and overall survival (OS) in patients with metastatic castration-resistant prostate cancer (mCRPC) treated with prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT). Pre-therapeutic laboratory and [68Ga]Ga-PSMA-11 PET/CT data of n = 102 mCRPC patients receiving [177Lu]Lu-PSMA-617 RLT within a prospective registry (REALITY Study, NCT04833517) were analyzed including laboratory parameters such as alkaline phosphatase (ALP), prostate-specific antigen (PSA), gamma glutamyl transferase (GGT), glutamate oxaloacetate transaminase (GOT), glutamate pyruvate transaminase (GPT), neuron specific enolase (NSE), hemoglobin (Hb), and imaging parameters such as maximum standardized uptake value of the tumor lesions (SUVmax), the mean standardized uptake value of all tumor lesions (SUVmean), the whole-body molecular tumor volume (MTV), and the whole-body total lesion PSMA (TLP). Mann-Whitney U test, univariate and multivariable Cox-regression were performed to test for association of the parameters with response and OS. The SUVmean of all lesions was significantly different between responders and non-responders (SUVmean responders 8.95 ± 2.83 vs. non-responders 7.88 ± 4.46, p = 0.003), whereas all other tested biochemical and imaging parameters did not reveal significant differences. Hb and the molecular imaging parameters MTV and TLP showed a significant association with OS (p = 0.013, p = 0.005; p = 0.009) in univariant Cox regression; however, only TLP remained significant in multivariable analysis (Hazard ratio 1.033, p = 0.009). This study demonstrates a statistically significant association between the quantitative PET/CT imaging parameter SUVmean and PSA response, as well as between the baseline TLP and OS of mCRPC patients undergoing RLT.

Molecular Mechanisms and Potential Predictive Biomarkers in Advanced Non-small Cell Lung Cancer: A Summary of Current and Future Trends

Non-small-cell lung cancer (NSCLC) accounts for 85% of lung cancer cases and is associated with different risk factors (smoking habits, gender, and age). In this scenario, many studies have been conducted to pursue improvement of survival, faster and better therapy response, reduced adverse events, and expanded available therapies and treatments against tumor resistance to drugs. These studies have focused on defining the most prevalent NSCLC biomarkers (EGFR, HER2, ALK, MET, ROS1, BRAF, KRAS G12C, HER3, NTRK, and NRG1) and their actionability. It is noteworthy that expressed kinase receptors can have overlapping mechanisms of activation of different pathways (JAK-STAT, MAPK, PI3K-AKT-mTOR, and PLC-c), which can lead to the same outcome of cell proliferation, migration, and survival resulting in increased tumor resistance to treatment. This review provides an overview of the latest findings regarding NSCLC treatment, emphasizing particular biomarkers and potential molecularly altered pathways implicated as targeted therapies. Additionally, it explores the clinical significance of the proposed treatments, their implication on progression-free survival, ongoing clinical trials, and their perspective of evolution so far.

Serum Caspase-3 Levels as a Predictive Molecular Biomarker for Acute Ischemic Stroke.

Caspases are key players in the apoptotic process and have been found to contribute to the pathogenesis of a variety of diseases, including neurological disorders such as ischemic stroke. This study aimed to investigate the serum levels of Caspase-3 in patients with acute ischemic stroke (AIS) and in control patients without ischemic events. Moreover, we explored any potential associations with the clinical outcomes of AIS. We enrolled 69 consecutive patients with clinical signs and symptoms of AIS in the presence of a negative CT scan who presented themselves at the Clinical Neurological Department from the Emergency Clinical Hospital of Galati within the first 24 h of symptom onset. The control group comprised 68 patients without cerebral ischemic pathologies. A comparison of the two groups showed significantly higher levels of caspase-3 at 24 and 48 h after hospital admission. No significant associations between caspase-3 levels and clinical features of AIS were seen. However, in a subgroup analysis conducted on patients with moderate/severe and severe stroke, lower levels of caspase-3 were associated with early mortality. Caspase-3 levels did not directly correlate with AIS severity or prognosis when considering all AIS patients. In patients with moderate to severe National Institute of Health Stroke Scale (NIHSS) scores, caspase-3 might be a prognostic indicator of early death. Further studies are required to confirm these results and further explore the mechanisms behind these findings.

Aqueous VEGF-A Levels as a Liquid Biopsy Biomarker of Retinoblastoma Vitreous Seed Response to Therapy.

Regression of retinoblastoma vitreous seeds (VS) during intravitreal chemotherapy can be delayed, resulting in supernumerary injections. Similarly, VS relapse may not be clinically evident at first. A predictive biomarker of tumor regression and relapse could help guide real-time clinical decision making. Retinoblastoma is an oxygen-sensitive tumor; paradoxically, VS survive in the hypoxic vitreous. We hypothesized that VS elaborate pro-angiogenic cytokines. The purpose was to determine if pro-angiogenic cytokine signatures from aqueous humor could serve as a biomarker of VS response to treatment. Multiplex ELISA was performed on aqueous from rabbit eyes with human retinoblastoma VS xenografts to identify expressed proangiogenic cytokines and changes in aqueous cytokine levels during intravitreal treatment were determined. Confirmatory RNAscope in situ hybridization for VEGF-A was performed on human retinoblastoma tumor sections and VS xenografts from rabbits. For human eyes undergoing intravitreal chemotherapy, serial aqueous VEGF-A levels measured via VEGF-A-specific ELISA were compared to clinical response. VEGF-A was highly expressed in human retinoblastoma VS in the xenograft model, and was the only proangiogenic cytokine that correlated with VS disease burden. In rabbits, aqueous VEGF-A levels decreased in response to therapy, consistent with quantitative VS reduction. In patients, aqueous VEGF-A levels associated with clinical changes in disease burden (regression, stability, or relapse), with changes in VEGF-A levels correlating with clinical response. Aqueous VEGF-A levels correlate with extent of retinoblastoma VS, suggesting that aqueous VEGF-A may serve as a predictive molecular biomarker of treatment response.

Diagnostic, predictive and prognostic molecular biomarkers in clear cell renal cell carcinoma: A retrospective study.

Clear cell renal cell carcinoma (ccRCC) is a common and aggressive subtype of kidney cancer. Many patients are diagnosed at advanced stages, making early detection crucial. Unfortunately, there are currently no noninvasive tests for ccRCC, emphasizing the need for new biomarkers. Additionally, ccRCC often develops resistance to treatments like radiotherapy and chemotherapy. Identifying biomarkers that predict treatment outcomes is vital for personalized care. The integration of artificial intelligence (AI), multi-omics analysis, and computational biology holds promise in bolstering detection precision and resilience, opening avenues for future investigations. The amalgamation of radiogenomics and biomaterial-basedimmunomodulation signifies a revolutionary breakthrough in diagnostic medicine. This review summarizes existing literature and highlights emerging biomarkers that enhance diagnostic, predictive, and prognostic capabilities for ccRCC, setting the stage for future clinical research.

Prediction of the survival status and tumor microenvironment in colorectal cancer through genotyping analysis based on toll-like receptors.

Colorectal cancer (CRC) ranks third in both the incidence and mortality rates among male and female cancers, and it is the leading digestive system cancer. Due to the inter- and intratumor heterogeneity of cancer, the TNM system is insufficient for predicting prognosis, necessitating the use of molecular biomarkers for prognostic prediction. Toll-like receptors (TLRs) have been associated with CRC survival rates. This study focused on the investigation of the role and potential value of TLRs in CRC genotyping to aid in immunotherapy for CRC patients. Differential gene expression analysis was performed on CRC transcriptomic data from The Cancer Genome Atlas database. TLRs were referred from the literature, and their intersection with differentially expressed genes (DEGs) in CRC yielded TLR-DEGs. The expression patterns of TLR-DEGs were predicted using the STRING website, and copy number variations of TLR-DEGs were analyzed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted on TLR-DEGs. ConsensusClusterPlus R package was used for clustering CRC patients, and ESTIMATE and GSEAbase were employed to analyze immune characteristics of different subtypes. Immune phenotyping scores and tumor immune dysfunction and exclusion scores were evaluated. DEGs of different subtypes were analyzed, followed by GO and KEGG enrichment analyses, the protein-protein interaction (PPI) network analysis, and further selection of hub genes. The sensitivity of drugs was assessed using the identified hub genes. We identified 37 TLR-DEGs, and the PPI analysis revealed their coexpression, although they were distributed on different chromosomes. Enrichment analyses indicated that the 37 TLR-DEGs were linked to cancer cell immune response. Based on these TLR-DEGs, CRC patients were classified into three subtypes. Cluster2 exhibited lower survival rates and higher immune infiltration levels and predicted poorer response to immune checkpoint inhibitor therapy. The intersection of DEGs from cluster2 and cluster1 with DEGs from cluster2 and cluster3 yielded a set of 426 commonly shared DEGs. Enrichment analyses revealed that these shared DEGs might regulate immune cell viability. Eight common hub genes for different subtypes were further identified to predict drug-related correlations. The developed TLR genotyping was used to predict the survival status and tumor microenvironment of CRC, providing a foundation for understanding the molecular mechanisms of TLR signaling and deepening its clinical significance.

Abstract PO4-15-05: Genomic characterization and molecular predictive biomarkers for chemotherapy in a real-world population with metastatic triple-negative breast cancer

Abstract Background: The genomic landscape of metastatic triple-negative breast cancer (mTNBC) in a real-world population is poorly defined and despite recent advances in precision oncology, molecular biomarkers for chemotherapy are largely lacking. The presence of specific genomic alterations and alterations in oncogenic pathways have the potential to provide prognostic as well as predictive information for chemotherapy, which remains the backbone treatment strategy for mTNBC. Methods: We conducted next-generation sequencing (NGS) with the FoundationOne CDx panel on tissue from the primary tumor and/or metastasis of 112 consecutive patients with mTNBC that were treated between 1998 and 2019 at 4 different Swedish hospitals. Every genomic alteration was, if applicable, subdivided into 1 of 10 canonical oncogenic pathways and noted for its involvement in the homologous recombination pathway (HRP). Frequently altered genes and pathways were then correlated with overall survival (OS) and evaluated regarding their association with progression-free survival (PFS) and response rate (RR) in patients treated with different chemotherapy agents. Tumor samples of patients with rapid progression or exceptional response to chemotherapy underwent exploratory comparison with regards to frequently altered genes and pathways and known clinical prognostic factors were compared between the two patient groups. Results: After excluding 15 patients due to insufficient quantity/quality of tumor tissue or absence of clinical data, 97 patients were analyzed. The median age at diagnosis of metastatic disease was 61 (range: 28-90), 80 % had visceral disease and 26 % received platinum-based chemotherapy in the first line setting. The most frequently altered genes were: TP53 (82 %), RAD21 (25 %), PIK3CA (23 %), MYC (22 %) and BRCA 1 or 2 (16 %). The most frequently altered pathways were TP53 (86 %), PI3K (60 %), RTK/RAS (47 %) and cell cycle (36 %). In total, 26 % of patients had an alteration in the HRP. None of the most frequently occurring genomic alterations were associated with OS. Variants of clinical significance in the HRP and BRCA1/BRCA2 genes were associated with a longer PFS in patients treated with platinum-based chemotherapy in the first line setting (HR 0.12-0.84 and 0.12-0.92). Exceptional responders to chemotherapy exhibited a more favorable clinical profile than rapid progressors (median age 51.5 vs 66.5, median Charlson comorbidity index 0.5 vs 3) whereas some numerical difference in the genomic profiling in terms of genomic alterations in MYC and RAS/RTK pathways (more often in exceptional responders) could be observed. Conclusions: We found no genomic alteration with prognostic significance in a cohort of mTNBC patients treated with chemotherapy in a real-world setting. Somatic variants of clinical significance in BRCA 1 and 2 and other HRP-related genes seem to define subgroups of patients with mTNBC that respond favorably to platinum-based chemotherapy. Further research into the genomic landscape of tumors from patients with rapid progression or exceptional response to specific treatment strategies can provide insights into mechanisms of resistance and identify new predictive biomarkers. Citation Format: Erik Olsson, Henrik Lindman, Evangelos Digkas, Viktoria Thurfjell, Haidar Mir Ali, Ute Krüger, Anna-Karin Wennstig, Marie Sundqvist, Antonis Valachis. Genomic characterization and molecular predictive biomarkers for chemotherapy in a real-world population with metastatic triple-negative breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-15-05.

Quality-Assured Analysis of PIK3CA Mutations in Hormone Receptor–Positive/Human Epidermal Growth Factor Receptor 2–Negative Breast Cancer Tissue

In precision oncology, reliable testing of predictive molecular biomarkers is the prerequisite for optimal patient treatment. Interlaboratory comparisons are a crucial tool to verify diagnostic performance and reproducibility of one's approach. Here, we describe the design and results of the first recurrent, internationally performed PIK3CA Breast Cancer Tissue external quality assessment (EQA), which was organized by German Quality in Pathology (QuIP) GmbH and started in 2021. After the internal pretesting phase performed by the (lead) panel institutes, in both 2021 and 2022, each EQA test set comprised n=10 tissue samples of hormone receptor-positive, human epidermal growth factor receptor 2-negative invasive breast cancer (IBC) that had to be analyzed and reported by the participants. In 2021, the results were evaluated separately for German-speaking countries (part 1) and international laboratories (part 2). In 2022, the EQA was performed across the European Union. The EQA success rates were 84.6% (n=11/13), 88.6% (n=39/44), and 87.9% (n=29/33) for EQA 2021 part 1, EQA 2021 part 2, and EQA 2022, respectively. The most commonly used methodologies were next-generation sequencing and mutation-/allele-specific qualitative polymerase-chain-reaction-based assays. In summary, this recurrent PIK3CA EQA proved to be a suitable approach for quality assessment in predictive molecular biomarker testing, to obtain an international overview of methods used for PIK3CA mutation analysis and to identify the strengths and weaknesses of individual methods.

Conserved immuno-collagenic subtypes predict response to immune checkpoint blockade.

Immune checkpoint blockade (ICB) has revolutionized the treatment of various cancer types. Despite significant preclinical advancements in understanding mechanisms, identifying the molecular basis and predictive biomarkers for clinical ICB responses remains challenging. Recent evidence, both preclinical and clinical, underscores the pivotal role of the extracellular matrix (ECM) in modulating immune cell infiltration and behaviors. This study aimed to create an innovative classifier that leverages ECM characteristics to enhance the effectiveness of ICB therapy. We analyzed transcriptomic collagen activity and immune signatures in 649 patients with cancer undergoing ICB therapy. This analysis led to the identification of three distinct immuno-collagenic subtypes predictive of ICB responses. We validated these subtypes using the transcriptome data from 9,363 cancer patients from The Cancer Genome Atlas (TCGA) dataset and 1,084 in-house samples. Additionally, novel therapeutic targets were identified based on these established immuno-collagenic subtypes. Our categorization divided tumors into three subtypes: "soft & hot" (low collagen activity and high immune infiltration), "armored & cold" (high collagen activity and low immune infiltration), and "quiescent" (low collagen activity and immune infiltration). Notably, "soft & hot" tumors exhibited the most robust response to ICB therapy across various cancer types. Mechanistically, inhibiting collagen augmented the response to ICB in preclinical models. Furthermore, these subtypes demonstrated associations with immune activity and prognostic predictive potential across multiple cancer types. Additionally, an unbiased approach identified B7 homolog 3 (B7-H3), an available drug target, as strongly expressed in "armored & cold" tumors, relating with poor prognosis. This study introduces histopathology-based universal immuno-collagenic subtypes capable of predicting ICB responses across diverse cancer types. These findings offer insights that could contribute to tailoring personalized immunotherapeutic strategies for patients with cancer.

Molecular and Clinicopathological Biomarkers in the Neoadjuvant Treatment of Patients with Advanced Resectable Melanoma.

Neoadjuvant systemic therapy is emerging as the best medical practice in patients with resectable stage III melanoma. As different regimens are expected to become available in this approach, the improved optimization of treatment strategies is required. Personalization of care in each individual patient-by precisely determining the disease-related risk and the most efficient therapeutic approach-is expected to minimize disease recurrence, but also the incidence of treatment-related adverse events and the extent of surgical intervention. This can be achieved through validation and clinical application of predictive and prognostic biomarkers. For immune checkpoint inhibitors, there are no validated predictive biomarkers until now. Promising predictive molecular biomarkers for neoadjuvant immunotherapy are tumor mutational burden and the interferon-gamma pathway expression signature. Pathological response to neoadjuvant treatment is a biomarker of a favorable prognosis and surrogate endpoint for recurrence-free survival in clinical trials. Despite the reliability of these biomarkers, risk stratification and response prediction in the neoadjuvant setting are still unsatisfactory and represent a critical knowledge gap, limiting the development of optimized personalized strategies in everyday practice.

Personalized decision support system for tailoring IgA nephropathy treatment strategies

BackgroundThe ongoing debate surrounding the use of immunosuppressive treatments for IgA nephropathy (IgAN) underscores the demand for personalized and effective strategies. MethodsAnalyzed data from 807 IgAN patients over 5+ years using three methods: Random Forest with molecular biomarkers, network biomarkers with graph engineering, and an auto-encoder model. All models were trained using identical demographic, clinical, and pathological data, employing an 80–20 split for training and testing purposes. ResultsIn the comprehensive assessment of IgAN prognosis, the Random Forest model, employing molecular biomarkers, demonstrated strong performance metrics (AUC = 0.83, sensitivity = 0.51, specificity = 0.96). However, traditional graph feature engineering on patient-specific networks outperformed these results with an AUC of 0.90, sensitivity of 0.64, and specificity of 0.94. The Auto-encoder model showed the best accuracy (AUC = 0.91, sensitivity = 0.46, specificity = 0.96). The findings highlighted the superior predictive capabilities of network biomarkers over molecular biomarkers for adverse renal outcome prediction in IgAN. Consequently, we integrated Auto-encoder-derived Network Biomarkers with Random Forest Models to enhance prognostic precision in diverse IgAN treatment scenarios. The prediction for the prognosis of patients receiving supportive care, glucocorticoid therapy, and immunosuppressant treatment yielded AUC values of 0.95, 0.96, and 1, respectively, indicating high specificity. Drawing from these insights, we pioneered the development of an innovative decision support model for IgAN treatment. This model demonstrated the ability to make medical decisions comparable to those by experienced nephrologists, enabling the customization of personalized disease management strategies. ConclusionOur system accurately predicted IgAN prognosis and evaluated various treatment efficacies, aiding physicians in devising optimal therapeutic strategies for patients.

Risk factors and predictive markers of post-stroke cognitive decline-A mini review.

Stroke is one of the top causes of death and disability worldwide. Cognitive impairments are found in more than 70% of individuals who have survived a stroke. Cognitive decline is a major contributor to disability, dependency, and morbidity. The prevalence and severity of dementia vary depending on different characteristics of the stroke and other clinical risk factors. Here we discuss the effects of stroke territory, patients' age, sex, cerebral blood flow, acute reperfusion therapy, and cognitive reserve of post-stroke cognitive decline. Potential predictive molecular and genetic biomarkers of post-stroke cognitive impairments are also discussed.

Immune checkpoint inhibitor-induced epidermal necrolysis: A narrative review evaluating demographics, clinical features, and culprit medications.

Immune checkpoint inhibitors (ICIs) have transformed cancer treatment but can cause immune-related adverse events (irAEs). Severe cutaneous irAEs, including epidermal necrolysis, are rare but potentially life-threatening. There is limited understanding of the clinical features and management of ICI-induced Stevens-Johnson syndrome (SJS)/toxic epidermal necrolysis (TEN), so we aimed to analyze 95 cases of ICI-induced SJS/TEN (35 cases of SJS, 26 cases of TEN, two cases of SJS/TEN overlap, and 32 cases of unspecified) to increase knowledge of this condition among oncologists and dermatologists. We conducted a comprehensive search of PubMed for all relevant case reports published until the end of December 2022, and collected data on patient demographics, cancer type, ICI regimen, time to onset of SJS/TEN, clinical presentation, management strategies, and outcomes. PD-1 inhibitors were the most common ICIs associated with SJS/TEN (58.9%), followed by the combination of PD-1 and CTLA-4 inhibitors (11.6%), and PD-L1 inhibitors (6.3%). Lung cancer and melanoma were the most frequent malignancies treated (35.8% and 25.4%, respectively). SJS/TEN occurred most frequently within the first 4 weeks (51.7%), and corticosteroid monotherapy was the most commonly chosen systemic treatment (56.4%). The overall mortality rate of ICI-induced SJS/TEN was 30.8%. Our findings highlight the frequency and severity of ICI-induced SJS/TEN and the urgent need for predictive molecular biomarkers aimed at preventive measures and early intervention.

Prospective Characterization of Circulating Tumor Cell Kinetics in Patients With Oligometastatic Disease Receiving Definitive Intent Radiation Therapy.

There are currently no predictive molecular biomarkers to identify patients with oligometastatic disease (OMD) who will benefit from definitive-intent radiation therapy (RT). We prospectively characterized circulating tumor cell (CTC) kinetics in patients with OMD undergoing definitive-intent RT. This prospective correlative biomarker study included patients with any solid malignancy ≤5 metastatic sites in ≤3 anatomic organ systems undergoing definitive-intent RT to all disease sites. Circulating tumor cells (CTCs) were captured and enumerated using a biomimetic cell rolling and nanotechnology-based assay functionalized with antibodies against epithelial cell adhesion molecule, against human epidermal growth factor receptor 2, and against epidermal growth factor receptor before and during RT and at follow-up visits up to 2 years post-RT. We enrolled 43 patients with a median follow-up of 14.3 months. The pretreatment CTC level (cells captured/mL) was not associated with the number of disease sites (median one metastatic site/patient, range 1-5) or metastasis location (bone, brain, visceral) on Wilcoxon signed-rank test, P > .05. Post-RT, 56% of patients received systemic therapy, and 72% of patients experienced subsequent local or systemic progression. For 90% of patients, a CTC level <15 within 130 days post-RT corresponded to a durable control of irradiated lesions. Patients with a favorable versus an unfavorable clearance profile experienced significantly longer progression-free survival after RT (median 13 v 4 months, log-rank test, P = .0011). On logistic regression, CTC level >15 at a given time point was associated with clinical disease progression within the subsequent 6 months (odds ratio 3.31, P = .007). In 26% of patients with disease progression, a CTC level >15 preceded radiographic or clinical progression. CTCs may serve as a biomarker for disease control in OMD and may predict disease progression before standard assessments for patients receiving diverse cancer-directed therapies.