Circulating Blood Prognostic Biomarker Signatures for Hemorrhagic Cerebral Cavernous Malformations (CCMs).

Cerebral cavernous malformations (CCMs) are a neurological disorder characterized by enlarged intracranial capillaries in the brain, increasing the susceptibility to hemorrhagic strokes, a major cause of death and disability worldwide. The limited treatment options for CCMs underscore the importance of prognostic biomarkers to predict the likelihood of hemorrhagic events, aiding in treatment decisions and identifying potential pharmacological targets. This study aimed to identify blood biomarkers capable of diagnosing and predicting the risk of hemorrhage in CCM1 patients, establishing an initial set of circulating biomarker signatures. By analyzing proteomic profiles from both human and mouse CCM models and conducting pathway enrichment analyses, we compared groups to identify potential blood biomarkers with statistical significance. Specific candidate biomarkers primarily associated with metabolism and blood clotting pathways were identified. These biomarkers show promise as prognostic indicators for CCM1 deficiency and the risk of hemorrhagic stroke, strongly correlating with the likelihood of hemorrhagic cerebral cavernous malformations (CCMs). This lays the groundwork for further investigation into blood biomarkers to assess the risk of hemorrhagic CCMs.

Exploring the Role of Circulating Cell-Free RNA in the Development of Colorectal Cancer.

Circulating tumor RNA (ctRNA) has recently emerged as a novel and attractive liquid biomarker. CtRNA is capable of providing important information about the expression of a variety of target genes noninvasively, without the need for biopsies, through the use of circulating RNA sequencing. The overexpression of cancer-specific transcripts increases the tumor-derived RNA signal, which overcomes limitations due to low quantities of circulating tumor DNA (ctDNA). The purpose of this work is to present an up-to-date review of current knowledge regarding ctRNAs and their status as biomarkers to address the diagnosis, prognosis, prediction, and drug resistance of colorectal cancer. The final section of the article discusses the practical aspects involved in analyzing plasma ctRNA, including storage and isolation, detection technologies, and their limitations in clinical applications.

Discussion on "Correct and logical causal inference for binary and time-to-event outcomes in randomized controlled trials" by Yi Liu, Bushi Wang, Miao Yang, Jianan Hui, Heng Xu, Siyoen Kil, and Jason C. Hsu.

In their paper, Liu et al. (2020) pointed out illogical discrepancies between subgroup and overall causal effects for some efficacy measures, in particular the odds and hazard ratios. As the authors show, the culprit is subgroups having prognostic effects within treatment arms. In response to their provocative findings, we found that the odds and hazard ratios are logic respecting when the subgroups are purely predictive, that is, the distribution of the potential outcome for the control treatment is homogeneous across subgroups. We also found that when we redefined the odds and hazards ratio causal estimands in terms of the joint distribution of the potential outcomes, the discrepancies are resolved under specific models in which the potential outcomes are conditionally independent. In response to other discussion points in the paper, we also provide remarks on association versus causation, confounding, statistical computing software, and dichotomania.

Technical Validation and Clinical Implications of Ultrasensitive PCR Approaches for EGFR-Thr790Met Mutation Detection in Pretreatment FFPE Samples and in Liquid Biopsies from Non-Small Cell Lung Cancer Patients.

In pretreatment tumor samples of EGFR-mutated non-small cell lung cancer (NSCLC) patients, EGFR-Thr790Met mutation has been detected in a variable prevalence by different ultrasensitive assays with controversial prognostic value. Furthermore, its detection in liquid biopsy (LB) samples remains challenging, being hampered by the shortage of circulating tumor DNA (ctDNA). Here, we describe the technical validation and clinical implications of a real-time PCR with peptide nucleic acid (PNA-Clamp) and digital droplet PCR (ddPCR) for EGFR-Thr790Met detection in diagnosis FFPE samples and in LB. Limit of blank (LOB) and limit of detection (LOD) were established by analyzing negative and low variant allele frequency (VAF) FFPE and LB specimens. In a cohort of 78 FFPE samples, both techniques showed an overall agreement (OA) of 94.20%. EGFR-Thr790Met was detected in 26.47% of cases and was associated with better progression-free survival (PFS) (16.83 ± 7.76 vs. 11.47 ± 1.83 months; p = 0.047). In LB, ddPCR was implemented in routine diagnostics under UNE-EN ISO 15189:2013 accreditation, increasing the detection rate of 32.43% by conventional methods up to 45.95%. During follow-up, ddPCR detected EGFR-Thr790Met up to 7 months before radiological progression. Extensively validated ultrasensitive assays might decipher the utility of pretreatment EGFR-Thr790Met and improve its detection rate in LB studies, even anticipating radiological progression.

Gut microbiome and its role in colorectal cancer.

Colorectal cancer (CRC) is still one of the most common types of cancer in the world, and the gut microbiome plays an important role in its development. The microbiome is involved in the carcinogenesis, formation and progression of CRC as well as its response to different systemic therapies. The composition of bacterial strains and the influence of geography, race, sex, and diet on the composition of the microbiome serve as important information for screening, early detection and prediction of the treatment outcome of CRC.Microbiome modulation is one of the most prospective new strategies in medicine to improve the health of individuals. Therefore, future research and clinical trials on the gut microbiome in oncology as well as in the treatment of CRC patients are warranted to determine the efficacy of systemic treatments for CRC, minimize adverse effects and increase survival rates.

Matrix metalloproteases and TIMPs as prognostic biomarkers in breast cancer patients treated with radiotherapy: A pilot study.

Breast cancer (BC) is the most common tumour in women and one of the most important causes of cancer death worldwide. Radiation therapy (RT) is widely used for BC treatment. Some proteins have been identified as prognostic factors for BC (Ki67, p53, E-cadherin, HER2). In the last years, it has been shown that variations in the expression of MMPs and TIMPs may contribute to the development of BC. The aim of this pilot work was to study the effects of RT on different MMPs (-1, -2, -3, -7, -8, -9, -10, -12 and -13) and TIMPs (-1 to -4), as well as their relationship with other variables related to patient characteristics and tumour biology. A group of 20 BC patients treated with RT were recruited. MMP and TIMP serum levels were analysed by immunoassay before, during and after RT. Our pilot study showed a slight increase in the levels of most MMP and TIMP with RT. However, RT produced a significantly decrease in TIMP-1 and TIMP-3 levels. Significant correlations were found between MMP-3 and TIMP-4 levels, and some of the variables studied related to patient characteristics and tumour biology. Moreover, MMP-9 and TIMP-3 levels could be predictive of RT toxicity. For this reason, MMP-3, MMP-9, TIMP-3 and TIMP-4 could be used as potential prognostic and predictive biomarkers for BC patients treated with RT.

Identifying prognostic biomarkers for palbociclib add-on therapy in fulvestrant-resistant breast cancer using cell-free DNA sequencing.

BACKGROUND: The FUTURE trial (UMIN000029294) demonstrated the safety and efficacy of adding palbociclib after fulvestrant resistance in patients with hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) advanced and metastatic breast cancer (ABC/MBC). In this planned sub-study, cancer panel sequencing of cell-free DNA (cfDNA) was utilized to explore prognostic and predictive biomarkers for further palbociclib treatment following fulvestrant resistance. MATERIALS AND METHODS: Herein, 149 cfDNA samples from 65 patients with fulvestrant-resistant disease were analysed at the time of palbociclib addition after fulvestrant resistance (baseline), on day 15 of cycle 1, and at the end of treatment using the assay for identifying diverse mutations in 34 cancer-related genes. RESULTS: During the course of treatment, mutations in ESR1, PIK3CA, FOXA1, RUNX1, TBX3, and TP53 were the most common genomic alterations observed. Analysis of genomic mutations revealed that before fulvestrant introduction, baseline PIK3CA mutations were marginally lower in metastatic aromatase inhibitor (AI)-treated patients compared to adjuvant AI-treated patients (P = 0.063). Baseline PIK3CA mutations were associated with poorer progression-free survival [hazard ratio: 1.62, P = 0.04]. Comparative analysis between baseline and early-changing gene mutations identified poor prognostic factors including early-changing MAP3K1 mutations (hazard ratio: 4.66, P = 0.04), baseline AR mutations (hazard ratio: 3.53, P = 0.04), and baseline PIK3CA mutations (hazard ratio: 3.41, P = 0.02). Notably, the relationship between ESR1 mutations and mutations in PIK3CA, MAP3K1, and TP53 weakened as treatment progressed. Instead, PIK3CA mutations became correlated with TP53 and FOXA1 mutations. CONCLUSIONS: Cancer panel testing for cfDNA identified prognostic and predictive biomarkers for palbociclib add-on therapy after acquiring fulvestrant resistance in patients with HR+/HER2- ABC/MBC.

Developmental-status-aware transcriptional decomposition establishes a cell state panorama of human cancers.

BACKGROUND: Cancer cells evolve under unique functional adaptations that unlock transcriptional programs embedded in adult stem and progenitor-like cells for progression, metastasis, and therapeutic resistance. However, it remains challenging to quantify the stemness-aware cell state of a tumor based on its gene expression profile. METHODS: We develop a developmental-status-aware transcriptional decomposition strategy using single-cell RNA-sequencing-derived tissue-specific fetal and adult cell signatures as anchors. We apply our method to various biological contexts, including developing human organs, adult human tissues, experimentally induced differentiation cultures, and bulk human tumors, to benchmark its performance and to reveal novel biology of entangled developmental signaling in oncogenic processes. RESULTS: Our strategy successfully captures complex dynamics in developmental tissue bulks, reveals remarkable cellular heterogeneity in adult tissues, and resolves the ambiguity of cell identities in in vitro transformations. Applying it to large patient cohorts of bulk RNA-seq, we identify clinically relevant cell-of-origin patterns and observe that decomposed fetal cell signals significantly increase in tumors versus normal tissues and metastases versus primary tumors. Across cancer types, the inferred fetal-state strength outperforms published stemness indices in predicting patient survival and confers substantially improved predictive power for therapeutic responses. CONCLUSIONS: Our study not only provides a general approach to quantifying developmental-status-aware cell states of bulk samples but also constructs an information-rich, biologically interpretable, cell-state panorama of human cancers, enabling diverse translational applications.

Tacrolimus in the treatment of childhood nephrotic syndrome: Machine learning detects novel biomarkers and predicts efficacy.

STUDY OBJECTIVE: The pharmacokinetics and pharmacodynamics of tacrolimus (TAC) vary greatly among individuals, hindering its precise utilization. Moreover, effective models for the early prediction of TAC efficacy in patients with nephrotic syndrome (NS) are lacking. We aimed to identify key factors affecting TAC efficacy and develop efficacy prediction models for childhood NS using machine learning algorithms. DESIGN: This was an observational cohort study of patients with pediatric refractory NS. SETTING: Guangzhou Women and Children's Medical Center between June 2013 and December 2018. PATIENTS: 203 patients with pediatric refractory NS were used for model generation and 35 patients were used for model validation. INTERVENTION: All patients regularly received double immunosuppressive therapy comprising TAC and low-dose prednisone or methylprednisolone. In this observational cohort study of 203 pediatric patients with refractory NS, clinical and genetic variables, including single-nucleotide polymorphism (SNPs), were identified. TAC efficacy was evaluated 3 months after administration according to two different evaluation criteria: response or non-response (Group 1) and complete remission, partial remission, or non-remission (Group 2). MEASUREMENTS: Logistic regression, extremely random trees, gradient boosting decision trees, random forest, and extreme gradient boosting algorithms were used to develop and validate the models. Prediction models were validated among a cohort of 35 patients with NS. MAIN RESULTS: The random forest models performed best in both groups, and the area under the receiver operating characteristics curve of these two models was 80.7% (Group 1) and 80.3% (Group 2). These prediction models included urine erythrocyte count before administration, steroid types, and eight SNPs (ITGB4 rs2290460, TRPC6 rs3824934, CTGF rs9399005, IL13 rs20541, NFKBIA rs8904, NFKBIA rs8016947, MAP3K11 rs7946115, and SMARCAL1 rs11886806). CONCLUSIONS: Two pre-administration models with good predictive performance for TAC response of patients with NS were developed and validated using machine learning algorithms. These accurate models could assist clinicians in predicting TAC efficacy in pediatric patients with NS before utilization to avoid treatment failure or adverse effects.

Prognostic Role of Circulating Tumor Cell Trajectories in Metastatic Colorectal Cancer.

BACKGROUND: A large amount of evidence from clinical studies has demonstrated that circulating tumor cells are strong predictors of outcomes in many cancers. However, the clinical significance of CTC enumeration in metastatic colorectal cancer is still questioned. The aim of this study was to evaluate the clinical value of CTC dynamics in mCRC patients receiving first-line treatments. MATERIALS AND METHODS: Serial CTC data from 218 patients were used to identify CTC trajectory patterns during the course of treatment. CTCs were evaluated at baseline, at a first-time point check and at the radiological progression of the disease. CTC dynamics were correlated with clinical endpoints. RESULTS: Using a cut-off of ≥1 CTC/7.5 mL, four prognostic trajectories were outlined. The best prognosis was obtained for patients with no evidence of CTCs at any timepoints, with a significant difference compared to all other groups. Lower PFS and OS were recognized in group 4 (CTCs always positive) at 7 and 16 months, respectively. CONCLUSIONS: We confirmed the clinical value of CTC positivity, even with only one cell detected. CTC trajectories are better prognostic indicators than CTC enumeration at baseline. The reported prognostic groups might help to improve risk stratification, providing potential biomarkers to monitor first-line treatments.

A Review of the Role of Oral Microbiome in the Development, Detection, and Management of Head and Neck Squamous Cell Cancers.

The role of the microbiome in the development and propagation of head and neck squamous cell cancer (HNSCC) is largely unknown and the surrounding knowledge lags behind what has been discovered related to the microbiome and other malignancies. In this review, the authors performed a structured analysis of the available literature from several databases. The authors discuss the merits and detriments of several studies discussing the microbiome of the structures of the aerodigestive system throughout the development of HNSCC, the role of the microbiome in the development of malignancies (generally and in HNSCC) and clinical applications of the microbiome in HNSCC. Further studies will be needed to adequately describe the relationship between HNSCC and the microbiome, and to push this relationship into a space where it is clinically relevant outside of a research environment.

Single B Cell Gene Co-Expression Networks Implicated in Prognosis, Proliferation, and Therapeutic Responses in Non-Small Cell Lung Cancer Bulk Tumors.

In NSCLC, there is a pressing need for immunotherapy predictive biomarkers. The processes underlying B-cell dysfunction, as well as their prognostic importance in NSCLC, are unknown. Tumor-specific B-cell gene co-expression networks were constructed by comparing the Boolean implication modeling of single-cell RNA sequencing of NSCLC tumor B cells and normal B cells. Proliferation genes were selected from the networks using in vitro CRISPR-Cas9/RNA interfering (RNAi) screening data in more than 92 human NSCLC epithelial cell lines. The prognostic and predictive evaluation was performed using public NSCLC transcriptome and proteome profiles. A B cell proliferation and prognostic gene co-expression network was present only in normal lung B cells and missing in NSCLC tumor B cells. A nine-gene signature was identified from this B cell network that provided accurate prognostic stratification using bulk NSCLC tumor transcriptome (n = 1313) and proteome profiles (n = 103). Multiple genes (HLA-DRA, HLA-DRB1, OAS1, and CD74) differentially expressed in NSCLC B cells, peripheral blood lymphocytes, and tumor T cells had concordant prognostic indications at the mRNA and protein expression levels. The selected genes were associated with drug sensitivity/resistance to 10 commonly used NSCLC therapeutic regimens. Lestaurtinib was discovered as a potential repositioning drug for treating NSCLC.

Prognostic features of the tumour microenvironment in oesophageal adenocarcinoma.

Oesophageal adenocarcinoma (OAC) is a disease with an incredibly poor survival rate and a complex makeup. The growth and spread of OAC tumours are profoundly influenced by their surrounding microenvironment and the properties of the tumour itself. Constant crosstalk between the tumour and its microenvironment is key to the survival of the tumour and ultimately the death of the patient. The tumour microenvironment (TME) is composed of a complex milieu of cell types including cancer associated fibroblasts (CAFs) which make up the tumour stroma, endothelial cells which line blood and lymphatic vessels and infiltrating immune cell populations. These various cell types and the tumour constantly communicate through environmental cues including fluctuations in pH, hypoxia and the release of mitogens such as cytokines, chemokines and growth factors, many of which help promote malignant progression. Eventually clusters of tumour cells such as tumour buds break away and spread through the lymphatic system to nearby lymph nodes or enter the circulation forming secondary metastasis. Collectively, these factors need to be considered when assessing and treating patients clinically. This review aims to summarise the ways in which these various factors are currently assessed and how they relate to patient treatment and outcome at an individual level.

Pancreatic Cancer Meets Human Microbiota: Close Encounters of the Third Kind.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal types of cancer with a dismal prognosis. The five-year survival rate has not changed significantly in over 40 years. Current first-line treatments only offer a modest increase in overall survival in unselected populations, and there is an urgent need to personalize treatment in this aggressive disease and develop new therapeutic strategies. Evolving evidence suggests that the human microbiome impacts cancerogenesis and cancer resistance to therapy. The mechanism of action and interaction of microbiome and PDAC is still under investigation. Direct and indirect effects have been proposed, and the use of several microbiome signatures as predictive and prognostic biomarkers for pancreatic cancer are opening new therapeutic horizons. In this review, we provide an overview for the clinicians of studies describing the influence and associations of oral, gastrointestinal and intratumoral microbiota on PDAC development, progression and resistance to therapy and the potential use of microbiota as a diagnostic, prognostic and predictive biomarker for PDAC.

Deep Proteomic Analysis on Biobanked Paraffine-Archived Melanoma with Prognostic/Predictive Biomarker Read-Out.

The discovery of novel protein biomarkers in melanoma is crucial. Our introduction of formalin-fixed paraffin-embedded (FFPE) tumor protocol provides new opportunities to understand the progression of melanoma and open the possibility to screen thousands of FFPE samples deposited in tumor biobanks and available at hospital pathology departments. In our retrospective biobank pilot study, 90 FFPE samples from 77 patients were processed. Protein quantitation was performed by high-resolution mass spectrometry and validated by histopathologic analysis. The global protein expression formed six sample clusters. Proteins such as TRAF6 and ARMC10 were upregulated in clusters with enrichment for shorter survival, and proteins such as AIFI1 were upregulated in clusters with enrichment for longer survival. The cohort's heterogeneity was addressed by comparing primary and metastasis samples, as well comparing clinical stages. Within immunotherapy and targeted therapy subgroups, the upregulation of the VEGFA-VEGFR2 pathway, RNA splicing, increased activity of immune cells, extracellular matrix, and metabolic pathways were positively associated with patient outcome. To summarize, we were able to (i) link global protein expression profiles to survival, and they proved to be an independent prognostic indicator, as well as (ii) identify proteins that are potential predictors of a patient's response to immunotherapy and targeted therapy, suggesting new opportunities for precision medicine developments.

What's new in mesothelioma.

Malignant pleural mesothelioma is a neoplasm characterized by a very poor prognosis and medico-legal implications. Diagnosis, prognosis and therapy are often challenging and include several issues. Cytological diagnosis is frequently the first step of the diagnostic process, and although its sensitivity may be somewhat lower, diagnostic criteria should be taken into account. When effusion cytology is inconclusive for the diagnosis, tissue biopsies should be taken. Even if the morphologic criteria for deciding whether a mesothelial proliferation is a benign or a malignant process have been defined, the separation of benign from malignant mesothelial proliferation is often a difficult problem for the pathologist, particularly on small biopsies. Thirdly, when the diagnosis is made, despite many efforts have been made to identify possible new biomarkers for early diagnosis, prognostic stratification and also predictive tools should be defined. Nowadays, the main prognostic parameter is still represented by the histological subtype, having the epithelioid MPM a better outcome than the sarcomatoid or biphasic MPM. A nuclear grading system have been also proposed to stratify patient outcome. Reliable predictive biomarkers are still lacking in MPM and a personalized therapeutic concept is eagerly needed. Mesothelioma occurs mostly as sporadic cancer and the main risk factor is asbestos exposure, but it also occurs among blood relatives suggesting possible increased genetic susceptibility besides shared exposures. Recently the study of genetic predisposition syndrome raised new aspect in the occurrence of mesothelioma cases.This review summarize these most important issues.

Single-cell mass cytometry and machine learning predict relapse in childhood leukemia.

Improved insight into cancer cell populations responsible for treatment failure will lead to better outcomes for patients. We herein highlight a single-cell study of B-cell precursor acute lymphoblastic leukemia (BCP-ALL) at diagnosis that revealed hidden developmentally dependent cell signaling states uniquely associated with relapse.

Personalized medicine in pancreatic cancer: the revolution has begun.

Pancreatic ductal adenocarcinoma carries a dismal prognosis. Both chemotherapy and targeted therapies have been disappointing when administered to unselected populations. Recently, progress has been made in our understanding of the genomic landscape of this cancer which displays remarkable heterogeneity suggesting a reorientation of management and research strategies based on molecular characterization and adapted personalized therapy. Resectable disease offers new opportunities for translational research through functional imaging response evaluation and tumor tissue acquisition before and after neoadjuvant therapy. There is urgent need for clinical trials based on molecular profiling in pancreatic ductal adenocarcinoma. In this review we discuss opportunities and limitations of these new strategies, underlining the importance of tissue acquisition and integration of molecular biomarkers in future molecularly driven clinical trials.

Combination of p16(INK4a) /Ki67 immunocytology and HPV polymerase chain reaction for the noninvasive analysis of HPV involvement in head and neck cancer.

BACKGROUND: High-risk human papillomavirus (HPV) infection has been identified as a relevant risk for the development of head and neck squamous cell carcinomas (HNSCCs). As HPV status has also gained a role as a prognostic and predictive biomarker for this entity, there is a growing demand for valid HPV testing in HNSCC patients METHODS: Liquid-based cytological smears from 45 HNSCC and 20 control patients were collected and used for simultaneous immunocytochemical p16(INK4a) /Ki67 staining using a CINtec PLUS kit after the presence of tumor cells was verified in a Papanicolaou-stained slide. The same cytological suspension was used for the detection of HPV DNA by specific polymerase chain reaction (PCR). RESULTS: Tumor cells were detected in the swab material of 44 HNSCC patients corresponding to a sensitivity of 98% (44 of 45). PCR analysis revealed the presence of HPV DNA in the cytological suspension of 13 patients (13 of 65, 20%) with simultaneous p16(INK4a) /Ki67 expression by the tumor cells in 11 of these HPV DNA-positive samples (11 of 13, 85%) - a staining pattern that is strongly associated with a carcinogenic HPV infection. CONCLUSIONS: A simultaneous immunocytochemical detection of p16(INK4a) and Ki67 can reliably be performed on liquid-based cytological smears from HNSCC patients using a CINtec PLUS kit. In addition, the same cytological material can be used for the detection of HPV DNA by specific PCR. The combined results of both techniques enable better discrimination between latent and carcinogenic HPV infections as well as HPV-negative cases and thus can provide information on the prognosis of HNSCC patients and facilitate therapeutic decisions.

Genomic Analysis as the First Step toward Personalized Treatment in Renal Cell Carcinoma.

Drug resistance mechanisms in renal cell carcinoma (RCC) still remain elusive. Although most patients initially respond to targeted therapy, acquired resistance can still develop eventually. Most of the patients suffer from intrinsic (genetic) resistance as well, suggesting that there is substantial need to broaden our knowledge in the field of RCC genetics. As molecular abnormalities occur for various reasons, ranging from single nucleotide polymorphisms to large chromosomal defects, conducting whole-genome association studies using high-throughput techniques seems inevitable. In principle, data obtained via genome-wide research should be continued and performed on a large scale for the purposes of drug development and identification of biological pathways underlying cancerogenesis. Genetic alterations are mostly unique for each histological RCC subtype. According to recently published data, RCC is a highly heterogeneous tumor. In this paper, the authors discuss the following: (1) current state-of-the-art knowledge on the potential biomarkers of RCC subtypes; (2) significant obstacles encountered in the translational research on RCC; and (3) recent molecular findings that may have a crucial impact on future therapeutic approaches.