Importance of Predictive Biomarkers and Epigenetics in Health: Novel Solutions in Clinical Care

Abstract Introduction/Objective Chronic health issues precipitate from a myriad of origins. We underline three common underlying causes: cumulative repair deficits, oxidative damage and metabolic acidosis. A unique set of predictive biomarkers (PBs) addressing these aspects is presented that has been developed on the premise that epigenetics influence 92% and genetics influence the remaining 8% of health. Together with an individualized and personalized treatment plan, this approach has shown to provide best health outcomes. Methods (1) To tailor therapeutic management of chronic conditions, predictive tests that have a variance of 5% or less are used and their “least risk, most gain” goal values are adhered to instead of usual or normal statistical ranges. This helps confirm specific individual need and facilitates effective monitoring of outcome results. Repair deficit is measured by hsCRP, oxidative damage measured by homocysteine, Omega 3 index, and 8OhdG; immune intolerance indicated by lymphocyte response assays and metabolic acidosis indicated by urine pH assessment. (2) Individualized nutrient protocols are formulated based on predictive biomarker results. (3) A metabolically alkalinizing diet is initiated with the goal to providing a buffering effect on cellular chemistry. For example, dietary sugars and refined flours are the single biggest triggers of inflammation driving hyperinsulinemia leading to a biochemical cascade that alters gene expression promoting inflammation. Results This proactive approach is evidence based and has been shown to lower costs while enhancing individual outcomes when compared to current best standards of care, reducing risks, and adding “years to life and life to years.” Conclusion There is a difference between known tests and functional predictive tests—identifies individual epigenetic risks better. Least risk-highest gain goal values are more relevant than normal lab values. Choosing the right kind of high-sensitivity biomarkers and adopting an associated lifestyle plan can improve quality of clinical care.

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Chemo-immunotherapy as first-line treatment for small-cell lung cancer

Therapeutic Advances in Medical Oncology ◽

10.1177/1758835920980365 ◽

2020 ◽

Vol 12 ◽

pp. 175883592098036

Author(s):

Saira Farid ◽

Stephen V. Liu

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Predictive Biomarkers ◽

High Response Rate ◽

Small Cell ◽

Standards Of Care ◽

Small Cell Lung ◽

First Line ◽

Line Chemotherapy

Small-cell lung cancer (SCLC) is a highly lethal subtype of lung cancer. Despite concerted efforts over the past several decades, there have been limited therapeutic advances. Traditional chemotherapy offers a high response rate and rapid symptomatic improvement, but its benefit is fleeting, and relapse is quick and unforgiving. Immunotherapy has delivered improved outcomes for patients with many cancers and there was compelling rationale for development in SCLC. While initial efforts with cytotoxic T-lymphocyte protein-4 inhibitors failed to improve upon chemotherapy alone, the addition of programmed death ligand-1 (PD-L1) inhibitors to first-line chemotherapy finally provided long-awaited gains in survival. Atezolizumab, when added to carboplatin and etoposide, improved both progression-free survival and overall survival. Durvalumab, when added to platinum plus etoposide, similarly improved OS. Biomarker development has stalled as PD-L1 expression and tumor mutational burden have not been useful predictive biomarkers. However, based on the significant survival improvements, both atezolizumab and durvalumab were approved by the US Food and Drug Administration to be given with first-line chemotherapy, and these regimens represent the new standards of care for SCLC.

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Challenges and opportunities for ovarian cancer management in the epidemic of Covid-19: lessons learned from Wuhan, China

Journal of Ovarian Research ◽

10.1186/s13048-021-00784-2 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Zhilan Chen ◽

Chun Zhang ◽

Jiu Yin ◽

Xin Xin ◽

Hemei Li ◽

...

Keyword(s):

Ovarian Cancer ◽

Large Scale ◽

Treatment Plan ◽

Clinical Care ◽

Gynecologic Cancer ◽

Treatment Phase ◽

Tumor Stage ◽

Current Treatment ◽

Lessons Learned ◽

Cancer Management

AbstractChina and the rest of the world are experiencing an outbreak of the 2019 novel coronavirus disease (COVID-19). Patients with cancer are more susceptible to viral infection and are more likely to develop severe complications, as compared to healthy individuals. The growing spread of COVID-19 presents challenges for the clinical care of patients with gynecological malignancies. Ovarian debulking surgery combined with the frequent need for chemotherapy is most likely why ovarian cancer was rated as the gynecologic cancer most affected by COVID-19. Therefore, ovarian cancer presents a particular challenging task. Concerning the ovarian cancer studies with confirmed COVID-19 reported from large-scale general hospitals in Wuhan, we hold that the treatment plan was adjusted appropriately and an individualized remedy was implemented. The recommendations discussed here were developed mainly based on the experience from Wuhan. We advise that the management strategy for ovarian cancer patients should be adjusted in the light of the local epidemic situation and formulated according to the pathological type, tumor stage and the current treatment phase. Online medical service is an effective and convenient communication platform during the pandemic.

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BIOM-32. ENDOPLASMIC RETICULUM PROTEIN SSR3 DETERMINES AND PREDICTS RESPONSE TO PACLITAXEL IN BREAST CANCER AND GLIOBLASTOMA

Neuro-Oncology ◽

10.1093/neuonc/noab196.063 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi17-vi18

Author(s):

Crismita Dmello ◽

Aarón Sonabend ◽

Víctor Arrieta ◽

Daniel Zhang ◽

Deepak Kanojia ◽

...

Keyword(s):

Breast Cancer ◽

Endoplasmic Reticulum ◽

Glioma Cells ◽

Predictive Biomarkers ◽

Predictive Biomarker ◽

Precision Oncology ◽

Patient Response ◽

Knock Out ◽

Genome Wide ◽

A Genome

Abstract Paclitaxel (PTX) is one the most potent and commonly used chemotherapies for breast and pancreatic cancer. Given the potency of this drug for glioblastomas (GBM) several ongoing clinical trials are investigating means of enhancing delivery of PTX across the blood-brain barrier for this disease. In spite of the efficacy of PTX, individual tumors exhibit variable susceptibility to this drug, with response rate in the range of 30%-60%. To identify predictive biomarkers for response to PTX, we performed a genome-wide CRISPR knock-out screen using human glioma cells. The most enriched genes in the CRISPR screen underwent further selection based on their correlation with survival in the breast cancer patient cohorts treated with PTX and not in patients treated with other chemotherapies, a finding that was validated on a second independent patient cohort. This led to the discovery of endoplasmic reticulum (ER) protein SSR3 as a putative predictive biomarker for PTX. SSR3 protein levels showed positive correlation with response to PTX in breast cancer cells, glioma cells, in multiple intracranial glioma xenografts and in GBM patient derived explant cultures. Knockout of SSR3 turned the cells resistant to PTX while its overexpression sensitized the cells to PTX. In gliomas, SSR3-mediated susceptibility to PTX relates to modulation of phosphorylation of ER stress sensor IRE1α. Thus, by using genome-wide screen combined with patient response data, we discovered a biomarker that demonstrates causal and correlative relationship with response to PTX in breast cancer and GBM. Prospective validation of this biomarker is warranted for its broad implementation for precision oncology.

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Tissue Microarray from Cell Block Material (cbTMA)—An Additional Shot for Cytology in the Predictive Pathology Era: The PD-L1 Experience

Journal of Molecular Pathology ◽

10.3390/jmp3010002 ◽

2022 ◽

Vol 3 (1) ◽

pp. 15-23

Author(s):

Antonino Iaccarino ◽

Gennaro Acanfora ◽

Pasquale Pisapia ◽

Umberto Malapelle ◽

Claudio Bellevicine ◽

...

Keyword(s):

Tissue Microarray ◽

Large Scale ◽

Metastatic Lymph Node ◽

Predictive Biomarkers ◽

Predictive Biomarker ◽

Observer Agreement ◽

Cell Block ◽

Multicenter Studies ◽

Ffpe Samples ◽

Biomarker Testing

Generally, predictive biomarker tests are clinically validated on histological formalin-fixed, paraffin-embedded (FFPE) samples. In addition to FFPE samples, cytological samples have also emerged as a useful approach to detect predictive biomarkers. However, as of today, despite the promising results reported in the recent literature, their full implementation in routine clinical practice is still lagging owing to a lack of standardized preparatory protocols, challenging assessments of cyto-histological correlation, and variable inter-observer agreement. The aim of this report was to explore the possibility of implementing a large-scale validation of predictive biomarker testing on cytological material. To this aim, we evaluated the technical feasibility of PD-L1 assessment on a cell block (CB)-derived tissue microarray (cbTMA). Consecutive and unselected CBs prepared from metastatic lymph node fine-needle cytology (FNC) samples were retrospectively collected and used for TMA construction. PD-L1 immunohistochemistry (IHC) was carried out on cbTMA sections with the companion diagnostic kit SP263 assay. TMA contained 33 CB-derived cores. A total of 20 sections were hematoxylin and eosin (H&E) stained. Overall, 29 (88%) samples were visible at least in one H&E-stained slide. Four cases out of five sections stained with the SP263 assay (4/29, 13.8%) showed PD-L1 positivity in neoplastic and/or immune cells; remarkably, no unspecific background was observed. Although our study was based on a limited and non-selected series, our findings do provide proof of concept for the use of cbTMA in predictive biomarker testing on cytological material in large-scale post-clinical trial validation studies, multicenter studies, and quality control programs.

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Identification of predictive biomarker for immunotherapy by associating with CD8+T cell Infiltration in lung adenocarcinoma.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.e21177 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. e21177-e21177

Author(s):

Puyuan Xing ◽

Teng Li ◽

Han Wang ◽

Lin Yang ◽

Guoqiang Wang ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Predictive Biomarkers ◽

Tumor Infiltrating Lymphocytes ◽

Predictive Performance ◽

Predictive Biomarker ◽

Pooled Analysis ◽

The Cancer Genome Atlas ◽

T Cell Infiltration ◽

Or Groups ◽

Cancer Genome Atlas

e21177 Background: Tumor immune microenvironment (TIME) has been proved associated with response to immunotherapy(I/O). We hypothesized that screening potential mutation pattern which could significantly impact the tumor infiltrating lymphocytes(TILs) can help us to identify predictive biomarkers for I/O in Lung adenocarcinoma(LUAD). Methods: Multiple-dimensional data from The Cancer Genome Atlas LUAD cohort (n = 514) was used for building a mathematical model beween mutation signature and CD8+TIL score (based on MCP-counter). An independent public validation cohort (cohort 1: LUAD, n = 598) were used to assess the immunotherapeutic predictive performance of the potential mutation patterns. Results: Top 100 gene associated with CD8+TIL score were selected based on MC+ model which can provides the minimum non-convexity of the penalized loss given the level of bias. Seven TIME genes (SPTA1 coef 0.09; MET coef 0.02; HSD3B1 coef -0.00; STAT4 coef -0.01; EGFR coef -0.08; PIK3CB coef -0.08; KEAP1 coef -0.24) were generated by taking the intersection of the top 100 mutant genes and FoundationOne (F1) CDx NGS 315 genes panel and verified in cohort 1. Survival analysis showed that SPTA1mt was the only one that associated with both significantly longer PFS (median PFS 3.15 vs 2.89 months; HR 0.65; 95% CI 0.45 to 0.93; p = 0.02) and OS (median PFS 15.08 vs 7.36 months; HR 0.59; 95% CI 0.40 to 0.88; p = 0.01) for patients who received I/O compared with chemotherapy(CT) among seven TIME genes. In order to test our hypothesis fully, a pooled analysis of SPTA1mt (a core positive predictors of CD8+TILs) and KEAP1mt (a core negative predictors for CD8+TILs ) were conducted and yielded that co occurrence of SPTA1mt and KEAP1mt had a compound effects for TIME. The validation showed that co mutation with SPTA1mt was accompanied by an decrease HR for I/O vs. CT in both PFS (HR S+K vs. K only 0.59 vs 1.56) and OS (HR S+K vs. K only 0.39 vs 0.80) for KEAP1mt patients. Conclusions: Our data show that it is feasible to identify individuals or groups of individual with specific mutations to immunotherapy responses from TIME view. SPTA1mt was a core predictors for higher CD8+ TILs and can be identified as a predictive biomarker for benefit from I/O compared with CT. Prospective studies are warranted for further investigation.

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Harnessing biomarkers of response to improve therapy selection in esophago-gastric adenocarcinoma

Pharmacogenomics ◽

10.2217/pgs-2020-0090 ◽

2021 ◽

Author(s):

Caroline YK Fong ◽

Ian Chau

Keyword(s):

Patient Outcomes ◽

Tumor Heterogeneity ◽

Systemic Treatment ◽

Predictive Biomarkers ◽

Predictive Biomarker ◽

Molecular Characteristics ◽

Precision Oncology ◽

First Line ◽

Clinical Strategies ◽

Line Chemotherapy

Advanced esophago-gastric (OG) adenocarcinomas have a high mortality rate and new therapeutic options are urgently required. Despite recent advances in understanding the molecular characteristics of OG cancers, tumor heterogeneity poses a challenge in developing new therapeutics capable of improving patient outcomes. Consequently, chemotherapy remains the mainstay of systemic treatment, with the HER2 being the only predictive biomarker routinely targeted in clinical practice. Recent data indicate that immunotherapy will be incorporated into first-line chemotherapy, but further research is required to refine patient selection. This review will summarize the clinical strategies being evaluated to utilize our knowledge of predictive biomarkers with reference to novel therapeutics, and discuss the barriers to implementing precision oncology in OG adenocarcinoma.

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Circulating miRNAs as a Predictive Biomarker of the Progression from Prediabetes to Diabetes: Outcomes of a 5-Year Prospective Observational Study

Journal of Clinical Medicine ◽

10.3390/jcm9072184 ◽

2020 ◽

Vol 9 (7) ◽

pp. 2184 ◽

Cited By ~ 1

Author(s):

Iwona Sidorkiewicz ◽

Magdalena Niemira ◽

Katarzyna Maliszewska ◽

Anna Erol ◽

Agnieszka Bielska ◽

...

Keyword(s):

Pathway Analysis ◽

Mirna Target ◽

Target Genes ◽

Quantitative Polymerase Chain Reaction ◽

Area Under The Curve ◽

Predictive Biomarkers ◽

Predictive Biomarker ◽

Circulating Mirnas ◽

Serum Samples ◽

Roc Curve Analysis

Due to a global increase in the prevalence of type 2 diabetes mellitus (T2DM), there is an urgent need for early identification of prediabetes, as these people have the highest risk of developing diabetes. Circulating miRNAs have shown potential as progression biomarkers in other diseases. This study aimed to conduct a baseline comparison of serum-circulating miRNAs in prediabetic individuals, with the distinction between those who later progressed to T2DM and those who did not. The expression levels of 798 miRNAs using NanoString technology were examined. Spearman correlation, receiver operating characteristic (ROC) curve analysis, and logistic regression modeling were performed. Gene ontology (GO) and canonical pathway analysis were used to explore the biological functions of the miRNA target genes. The study revealed that three miRNAs were upregulated in the serum samples of patients who later progressed to T2DM. Pathway analysis showed that the miRNA target genes were mainly significantly enriched in neuronal NO synthase (nNOS) signaling in neurons, amyloid processing, and hepatic cholestasis. ROC analysis demonstrated that miR-491-5p, miR-1307-3p, and miR-298 can be introduced as a diagnostic tool for the prediction of T2DM (area under the curve (AUC) = 94.0%, 88.0%, and 84.0%, respectively). Validation by real-time quantitative polymerase chain reaction (qRT-PCR) confirmed our findings. The results suggest that circulating miRNAs can potentially be used as predictive biomarkers of T2DM in prediabetic patients.

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The mutational landscape of chronic lymphocytic leukemia and its impact on prognosis and treatment

Hematology ◽

10.1182/asheducation-2017.1.329 ◽

2017 ◽

Vol 2017 (1) ◽

pp. 329-337 ◽

Cited By ~ 19

Author(s):

Gianluca Gaidano ◽

Davide Rossi

Keyword(s):

Chronic Lymphocytic Leukemia ◽

Predictive Biomarkers ◽

Predictive Biomarker ◽

Treatment Choice ◽

Lymphocytic Leukemia ◽

Prognostic Scores ◽

Mutation Status ◽

Biological Variables ◽

Trisomy 12 ◽

Innovative Drugs

Abstract The typical genome of chronic lymphocytic leukemia (CLL) carries ∼2000 molecular lesions. Few mutations recur across patients at a frequency >5%, whereas a large number of biologically and clinically uncharacterized genes are mutated at lower frequency. Approximately 80% of CLL patients carry at least 1 of 4 common chromosomal alterations, namely deletion 13q14, deletion 11q22-23, deletion 17p12, and trisomy 12. Knowledge of the CLL genome has translated into the availability of molecular biomarkers for prognosis and treatment prediction. Prognostic biomarkers do not affect treatment choice, and can be integrated into prognostic scores that are based on both clinical and biological variables. Molecular predictive biomarkers affect treatment choice, and currently include TP53 disruption by mutation and/or deletion and IGHV mutation status. TP53 disruption by gene mutation and/or deletion associates with chemoimmunotherapy failure and mandates treatment with innovative drugs, including ibrutinib, idelalisib, or venetoclax. The mutation status of IGHV genes represents a predictive biomarker for identifying patients that may benefit the most from chemoimmunotherapy with fludarabine, cyclophosphamide, and rituximab. Assessment of these biomarkers at the time of treatment requirement is recommended by most current guidelines for CLL management. Other molecular predictors are under investigation, but their application in clinical practice is premature.

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Variation in clinical care associated with weekend admission and discharge in psychiatric in-patient units: retrospective case-note review

BJPsych Open ◽

10.1192/bjo.2020.88 ◽

2020 ◽

Vol 6 (5) ◽

Author(s):

Ryan Williams ◽

Lorna Farquharson ◽

Ellen Rhodes ◽

Mary Dang ◽

Natasha Lindsay ◽

...

Keyword(s):

Quality Of Care ◽

Psychiatric Hospital ◽

Depressive Disorders ◽

Clinical Care ◽

Case Note ◽

Weekend Effect ◽

Standards Of Care ◽

Retrospective Case ◽

Case Note Review

Background Questions have been raised regarding differences in the standards of care that patients receive when they are admitted to or discharged from in-patient units at weekends. Aims To compare the quality of care received by patients with anxiety and depressive disorders who were admitted to or discharged from psychiatric hospital at weekends with those admitted or discharged during the ‘working week’. Method Retrospective case-note review of 3795 admissions to in-patient psychiatric wards in England. Quality of care received by people with depressive or anxiety disorders was compared using multivariable regression analyses. Results In total, 795 (20.9%) patients were admitted at weekends and 157 (4.8%) were discharged at weekends. There were minimal differences in quality of care between those admitted at weekends and those admitted during the week. Patients discharged at weekends were less likely to be given sufficient notification (48 h) in advance of being discharged (OR = 0.55, 95% CI 0.39–0.78), to have a crisis plan in place (OR = 0.65, 95% CI 0.46–0.92) or to be given medication to take home (OR = 0.45, 95% CI 0.30–0.66). They were also less likely to have been assessed using a validated outcome measure (OR = 0.70, 95% CI 0.50–0.97). Conclusions There is no evidence of a ‘weekend effect’ for patients admitted to psychiatric hospital at weekends, but the quality of care offered to those who were discharged at weekends was relatively poor, highlighting the need for improvement in this area.

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