Digital histological markers based on routine H&E slides to predict benefit from maintenance immunotherapy in esophagogastric adenocarcinoma.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16074-e16074
Author(s):  
Quoc Dang Vu ◽  
Caroline Fong ◽  
Katharina von Loga ◽  
Shan E Ahmed Raza ◽  
Daniel Nava Rodrigues ◽  
...  
Keyword(s):  
Molecular Markers ◽  
Predictive Power ◽  
Low Cost ◽  
Predictive Biomarkers ◽  
Operating Characteristics ◽  
Treatment Benefit ◽  
Platinum Based Chemotherapy ◽  
Slide Image ◽  
Tumor Mutational Burden ◽  
Hematoxylin And Eosin

e16074 Background: Immune checkpoint inhibition (ICI) is an effective treatment for a subset of patients with inoperable esophagogastric (EG) adenocarcinoma. Robust predictive biomarkers are required to identify these patients and a variety of strategies including immunohistochemical staining of PD-L1 and tumor mutational burden (TMB) assessment have been employed. Here, we explore digital histological (dHis) markers based on routine hematoxylin and eosin (H&E) slides alone or in combination with molecular markers (PD-L1 and TMB) as predictive biomarkers of benefit from maintenance immunotherapy in patients with inoperable EG adenocarcinoma. Methods: We developed a deep learning based algorithm to construct novel digital histological (dHis) markers by summarizing the statistics of all different types of nuclei present in the tumor tissue sections, their morphological features and their colocalization across each of the whole slide image. The dHis markers were then input into a decision-tree based approach to test for prognostic and predictive power alone or in combination with molecular markers. We assessed two cohorts of patients randomized to surveillance (n=38) or maintenance durvalumab (n=35) after 18 weeks of first-line platinum-based chemotherapy in the PLATFORM trial (NCT02678182) according to the 12-week progression-free rate. We measured the accuracy as the area under the receiver operating characteristics curve (AUROC) to determine the prognostic and predictive power of each marker set. We conducted a stratified 3-fold cross-validation, repeated 5 times and report the overall AUROC results. Results: Molecular markers alone yielded an AUROC of 0.5581±0.0939 on the surveillance arm, 0.6671±0.1479 on the treatment arm, and 0.6376±0.0958 for both the arms. Digital histological markers alone yielded an AUROC of 0.8952±0.0638, 0.8995±0.0719 and 0.8488±0.0700 on surveillance, immunotherapy and both arms, respectively. When using these two sets of markers together for both arms, molecular markers offered a limited improvement (around 0.02). Patients with TMB in the highest tertile were associated with lower likelihood of having progressive disease 12 weeks after randomization. Interestingly, dHis markers from morphology of connective and inflammatory nuclei were highly predictive for treatment benefit. Conclusions: Preliminary results suggest digital histological markers offer significant improvement over PD-L1 and TMB markers alone for predicting benefit from immunotherapy in EG adenocarcinoma with the added advantages of scalable, rapid, low-cost and objective quantification on routine histology sections. We are further validating their effectiveness on a larger cohort. Clinical trial information: NCT02678182.

Predictive biomarkers for immunotherapy efficacy in non-small-cell lung cancer: current status and future perspectives

2020 ◽  
Vol 14 (14) ◽  
pp. 1383-1392
Author(s):  
Deniz C Guven ◽  
Taha K Sahin ◽  
Omer Dizdar ◽  
Saadettin Kilickap
Keyword(s):  
Checkpoint Inhibitors ◽  
Low Cost ◽  
Predictive Biomarkers ◽  
Current Status ◽  
Future Perspectives ◽  
Mutational Burden ◽  
Recent Developments ◽  
Tumor Mutational Burden ◽  
Ease Of Access ◽  
Nsclc Patients

In recent years, immune checkpoint inhibitors have rapidly changed treatment paradigms and have been pivotal for the treatment of advanced NSCLC patients. However, many patients don't respond to immunotherapy, and toxicities are a concern. Mounting evidence suggests that PD-L1 expression and tumor mutational burden are useful biomarkers in NSCLC and widely used in clinical practice. Given various limitations of PD-L1 and tumor mutational burden, many candidate biomarkers have emerged. From these biomarkers, peripheral blood-based biomarkers are promising options for the prediction of immunotherapy efficacy with ease of access, repeatability and low cost. This review provides an overview of recent developments on the biomarkers in immunotherapy efficacy together with comments on future perspectives.

scholarly journals Immunotherapy Predictive Molecular Markers in Advanced Gastroesophageal Cancer: MSI and Beyond

Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1715
Author(s):  
Robin Park ◽  
Laercio Lopes ◽  
Anwaar Saeed
Keyword(s):  
Treatment Options ◽  
Unmet Need ◽  
Predictive Biomarkers ◽  
Phase Iii ◽  
Gastroesophageal Cancer ◽  
Programmed Death ◽  
Phase Iii Trials ◽  
Tumor Mutational Burden ◽  
Large Phase ◽  
Programmed Death 1

Advanced gastroesophageal cancer (GEC) has a poor prognosis and limited treatment options. Immunotherapy including the anti-programmed death-1 (PD-1) antibodies pembrolizumab and nivolumab have been approved for use in various treatment settings in GEC. Additionally, frontline chemoimmunotherapy regimens have recently demonstrated promising efficacy in large phase III trials and have the potential to be added to the therapeutic armamentarium in the near future. There are currently several immunotherapy biomarkers that are validated for use in the clinical setting for GEC including programmed death ligand-1 (PD-L1) expression as well as the tumor agnostic biomarkers such as mismatch repair or microsatellite instability (MMR/MSI) and tumor mutational burden (TMB). However, apart from MMR/MSI, these biomarkers are imperfect because none are highly sensitive nor specific. Therefore, there is an unmet need for immunotherapy biomarker development. To this end, several biomarkers are currently being evaluated in ongoing trials with some showing promising predictive potential. Here, we summarize the landscape of immunotherapy predictive biomarkers that are currently being evaluated in GEC.

scholarly journals End-to-end convolutional neural network enables COVID-19 detection from breath and cough audio: a pilot study

2021 ◽  
Vol 7 (2) ◽  
pp. 356-362
Author(s):  
Harry Coppock ◽  
Alex Gaskell ◽  
Panagiotis Tzirakis ◽  
Alice Baird ◽  
Lyn Jones ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Low Cost ◽  
Area Under The Curve ◽  
Alternative Form ◽  
Economic Damage ◽  
Audio Signals ◽  
Operating Characteristics ◽  
Data Set ◽  
Empirical Performance

BackgroundSince the emergence of COVID-19 in December 2019, multidisciplinary research teams have wrestled with how best to control the pandemic in light of its considerable physical, psychological and economic damage. Mass testing has been advocated as a potential remedy; however, mass testing using physical tests is a costly and hard-to-scale solution.MethodsThis study demonstrates the feasibility of an alternative form of COVID-19 detection, harnessing digital technology through the use of audio biomarkers and deep learning. Specifically, we show that a deep neural network based model can be trained to detect symptomatic and asymptomatic COVID-19 cases using breath and cough audio recordings.ResultsOur model, a custom convolutional neural network, demonstrates strong empirical performance on a data set consisting of 355 crowdsourced participants, achieving an area under the curve of the receiver operating characteristics of 0.846 on the task of COVID-19 classification.ConclusionThis study offers a proof of concept for diagnosing COVID-19 using cough and breath audio signals and motivates a comprehensive follow-up research study on a wider data sample, given the evident advantages of a low-cost, highly scalable digital COVID-19 diagnostic tool.

scholarly journals Emerging Trends for Radio-Immunotherapy in Rectal Cancer

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1374
Author(s):  
Claudia Corrò ◽  
Valérie Dutoit ◽  
Thibaud Koessler
Keyword(s):  
Rectal Cancer ◽  
Tumor Microenvironment ◽  
Immune Checkpoint ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Tumor Infiltrating Lymphocytes ◽  
T Cell Infiltration ◽  
Emerging Trends ◽  
Tumor Mutational Burden ◽  
Microsatellite Stability

Rectal cancer is a heterogeneous disease at the genetic and molecular levels, both aspects having major repercussions on the tumor immune contexture. Whilst microsatellite status and tumor mutational load have been associated with response to immunotherapy, presence of tumor-infiltrating lymphocytes is one of the most powerful prognostic and predictive biomarkers. Yet, the majority of rectal cancers are characterized by microsatellite stability, low tumor mutational burden and poor T cell infiltration. Consequently, these tumors do not respond to immunotherapy and treatment largely relies on radiotherapy alone or in combination with chemotherapy followed by radical surgery. Importantly, pre-clinical and clinical studies suggest that radiotherapy can induce a complete reprograming of the tumor microenvironment, potentially sensitizing it for immune checkpoint inhibition. Nonetheless, growing evidence suggest that this synergistic effect strongly depends on radiotherapy dosing, fractionation and timing. Despite ongoing work, information about the radiotherapy regimen required to yield optimal clinical outcome when combined to checkpoint blockade remains largely unavailable. In this review, we describe the molecular and immune heterogeneity of rectal cancer and outline its prognostic value. In addition, we discuss the effect of radiotherapy on the tumor microenvironment, focusing on the mechanisms and benefits of its combination with immune checkpoint inhibitors.

scholarly journals Untargeted analysis of first trimester serum to reveal biomarkers of pregnancy complications: a case–control discovery phase study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
E. W. Harville ◽  
Y.-Y. Li ◽  
K. Pan ◽  
S. McRitchie ◽  
W. Pathmasiri ◽  
...  
Keyword(s):  
Pregnancy Complications ◽  
Predictive Power ◽  
Gestational Hypertension ◽  
Predictive Biomarkers ◽  
First Trimester ◽  
Resonance Spectroscopy ◽  
Renal Secretion ◽  
Global Alliance ◽  
Phase Study ◽  
High Resolution Mass Spectroscopy

AbstractUnderstanding of causal biology and predictive biomarkers are lacking for hypertensive disorders of pregnancy (HDP) and preterm birth (PTB). First-trimester serum specimens from 51 cases of HDP, including 18 cases of pre-eclampsia (PE) and 33 cases of gestational hypertension (GH); 53 cases of PTB; and 109 controls were obtained from the Global Alliance to Prevent Prematurity and Stillbirth repository. Metabotyping was conducted using liquid chromatography high resolution mass spectroscopy and nuclear magnetic resonance spectroscopy. Multivariable logistic regression was used to identify signals that differed between groups after controlling for confounders. Signals important to predicting HDP and PTB were matched to an in-house physical standards library and public databases. Pathway analysis was conducted using GeneGo MetaCore. Over 400 signals for endogenous and exogenous metabolites that differentiated cases and controls were identified or annotated, and models that included these signals produced substantial improvements in predictive power beyond models that only included known risk factors. Perturbations of the aminoacyl-tRNA biosynthesis, l-threonine, and renal secretion of organic electrolytes pathways were associated with both HDP and PTB, while pathways related to cholesterol transport and metabolism were associated with HDP. This untargeted metabolomics analysis identified signals and common pathways associated with pregnancy complications.

scholarly journals Incidental Squamous Cell Carcinoma in an Epidermal Inclusion Cyst: A Case Report and Review of the Literature

2018 ◽  
Vol 10 (1) ◽  
pp. 61-68 ◽  
Author(s):  
Ethan Frank ◽  
David Macias ◽  
Brian Hondorp ◽  
Justin Kerstetter ◽  
Jared C. Inman
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Low Cost ◽  
Neck Mass ◽  
Inclusion Cyst ◽  
Neoplastic Change ◽  
Epidermal Inclusion Cyst ◽  
Hematoxylin And Eosin ◽  
Well Differentiated

Epidermal inclusion cysts are common lesions that rarely develop into squamous cell carcinoma (SCC). Neoplastic change in these cysts can be associated with prominent symptoms such as pain, rapid growth, or ulceration. This study describes the case of a 64-year-old woman with a 4-year history of a largely asymptomatic neck mass, which after routine excision was found to be an epidermal inclusion cyst harboring well-differentiated SCC. The diagnosis was made incidentally after routine cyst bisection and hematoxylin and eosin staining. Given the potential for variable presentation and low cost of hematoxylin and eosin analysis, we recommend a low threshold for a comprehensive pathological search for malignancy in excised cysts when appropriate.

scholarly journals Nanopore Targeted Sequencing for Rapid Gene Mutations Detection in Acute Myeloid Leukemia

Genes ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 1026 ◽  
Author(s):  
Cumbo ◽  
Minervini ◽  
Orsini ◽  
Anelli ◽  
Zagaria ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Low Cost ◽  
Gene Mutations ◽  
Predictive Biomarkers ◽  
Molecular Testing ◽  
Sequencing Analysis ◽  
Cebpa Mutations ◽  
Targeted Gene Sequencing ◽  
Acute Myeloid

Acute myeloid leukemia (AML) clinical settings cannot do without molecular testing to confirm or rule out predictive biomarkers for prognostic stratification, in order to initiate or withhold targeted therapy. Next generation sequencing offers the advantage of the simultaneous investigation of numerous genes, but these methods remain expensive and time consuming. In this context, we present a nanopore-based assay for rapid (24 h) sequencing of six genes (NPM1, FLT3, CEBPA, TP53, IDH1 and IDH2) that are recurrently mutated in AML. The study included 22 AML patients at diagnosis; all data were compared with the results of S5 sequencing, and discordant variants were validated by Sanger sequencing. Nanopore approach showed substantial advantages in terms of speed and low cost. Furthermore, the ability to generate long reads allows a more accurate detection of longer FLT3 internal tandem duplications and phasing double CEBPA mutations. In conclusion, we propose a cheap, rapid workflow that can potentially enable all basic molecular biology laboratories to perform detailed targeted gene sequencing analysis in AML patients, in order to define their prognosis and the appropriate treatment.

scholarly journals Identification of Proteins Deregulated by Platinum-Based Chemotherapy as Novel Biomarkers and Therapeutic Targets in Non-Small Cell Lung Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Sarah-Louise Ryan ◽  
Keyur A. Dave ◽  
Sam Beard ◽  
Martina Gyimesi ◽  
Matthew McTaggart ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Cellular Response ◽  
Predictive Biomarkers ◽  
Small Cell ◽  
Learning Approaches ◽  
Small Cell Lung ◽  
Platinum Based Chemotherapy ◽  
Novel Biomarkers

Platinum-based chemotherapy remains the cornerstone of treatment for most people with non-small cell lung cancer (NSCLC), either as adjuvant therapy in combination with a second cytotoxic agent or in combination with immunotherapy. Resistance to therapy, either in the form of primary refractory disease or evolutionary resistance, remains a significant issue in the treatment of NSCLC. Hence, predictive biomarkers and novel combinational strategies are required to improve the effectiveness and durability of treatment response 6for people with NSCLC. The aim of this study was to identify novel biomarkers and/or druggable proteins from deregulated protein networks within non-oncogene driven disease that are involved in the cellular response to cisplatin. Following exposure of NSCLC cells to cisplatin, in vitro quantitative mass spectrometry was applied to identify altered protein response networks. A total of 65 proteins were significantly deregulated following cisplatin exposure. These proteins were assessed to determine if they are druggable targets using novel machine learning approaches and to identify whether these proteins might serve as prognosticators of platinum therapy. Our data demonstrate novel candidates and drug-like molecules warranting further investigation to improve response to platinum agents in NSCLC.

scholarly journals Anthropometric measurements as predictors of hypertension in Busia, Vihiga, Trans Nzoia and Siaya counties of Western Kenya

2021 ◽  
Author(s):  
Thomas Andale ◽  
Vitalis A. Orango ◽  
Gerald Omondi Lwande ◽  
Grace W Mwaura ◽  
Richard Mugo Ngari ◽  
...  
Keyword(s):  
Predictive Power ◽  
Anthropometric Measurements ◽  
Sub Saharan Africa ◽  
Operating Characteristics ◽  
Chi Square ◽  
Cross Sectional ◽  
Western Kenya ◽  
Reduced Physical Activity ◽  
Sub Saharan ◽  
Sensitivity Specificity

Emerging data suggest a rise in the incidence rate of hypertension in many countries within Sub-Saharan Africa. This has been attributed to socioeconomic factors that have influenced diet and reduced physical activity further deranging anthropometric measurements. We assessed the predictive power of three anthropometric indicators namely: waist circumference (WC), waist to height ratio (WHtR) and body mass index (BMI) in detecting hypertension. This cross-sectional community survey was conducted in four counties within Western Kenya between October 2018 to April 2019 among 3594 adults. The participants sociodemographic data were collected using an interviewer-administered questionnaire and anthropometric measurements taken. We used the R-software for descriptive and inferential statistical analysis. Pearson chi-square test was used to assess the association between anthropometric measurements and hypertension while logistic regressions estimated the likelihood of hypertension. Youden method was used to identify optimal anthropometric cut-offs for sensitivity, specificity and area under the receiver operating characteristics (ROC) curve computation. The crude prevalence of hypertension was 23.3%, however it rose with advancement in age. Furthermore, obese individuals had a three-fold (AOR=2.64; 95% CI: 2.09, 3.35) increased likelihood of hypertension compared to those with a normal BMI. The optimal WC cut-off was 82.5cm for men and 87cm for women, an optimal WHtR of 0.47 for men and 0.55 for women; while the optimal BMI cut-off was 23.7 kg/m2 and 22.6 kg/m2 for men and women respectively. The sensitivity of WC, WHtR and BMI for men was 0.60, 0.65 and 0.39 respectively and 0.71, 0.65 and 0.78 respectively for women. BMI is the best predictor for hypertension among women but a poor predictor for men; WC had a high hypertension predictive power for both gender while WHtR is the best hypertension predictor for men.

Automated immunostaining-free prediction of breast carcinoma ER and PR status, Ki67 count, patient therapy stratification index and quantification of prognostic quiescence burden in TNBC from pretreatment H&E stained histopathology images in breast cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12535-e12535
Author(s):  
Tathagata Dasgupta ◽  
Satabhisa Mukhopadhyay ◽  
Nicolas M Orsi ◽  
Michele Cummings ◽  
Angelene Berwick
Keyword(s):  
Low Cost ◽  
A Priori ◽  
Disease Recurrence ◽  
Mitotic Checkpoint ◽  
Luminal A ◽  
Slide Image ◽  
Luminal Type ◽  
Therapy Stratification ◽  
Pre Treatment ◽  
Stratification System

e12535 Background: Categorical combinations of ER, PR, HER2, and Ki67 levels are traditionally used to classify patients into luminal A and B-like subtypes in order to inform treatment choice. Accounting for nearly 70% of all breast malignancies, luminal cancer is heterogeneous, harboring subtypes with distinct molecular profiles and clinical outcomes. Although most patients with luminal-type disease respond well to endocrine therapy alone, some develop recurrences benefiting from additional cytotoxic therapy. Identifying such cases a priori remains a challenge but would enable patients to be spared the debilitating side-effects of ineffective chemotherapy. In this regard, the efficacy of chemotherapy and disease recurrence relate to (i) ER driven G1/S perturbations and/or (ii) quiescent cell populations arrested in the G0/G1 phase of cell cycle. This study aimed to develop a histopathology whole slide image (WSI)-based, low cost, rapid and automated approach to: (i) predict ER/PR/Ki67 status, (ii) quantify quiescence burden, (iii) develop a G1/S-based patient stratification system for luminal A/B patients, and (iv) achieve a quiescence burden-based stratification of TNBC patients. Methods: This investigation centered on the initial clinical validation of a novel, immunostaining-free technology which uses information extracted from pre-treatment hematoxylin and eosin (H&E) stained slide WSIs alone to achieve these aims. Unlike conventional artificial intelligence-based approaches, the underlying proprietary algorithm and its prediction criteria are based on deterministic, hard-coded observational relationships of continuous scales drawn from WSI morphological features. In this instance, these represent tumor-related biological pathway disruptions and mitotic checkpoint perturbations, where G1/S perturbations enable luminal subtype stratification, and G0/G1 perturbations reflect quiescence burden. Back projecting the algorithm’s quiescence burden output on to the original WSIs enables morphological patterns to be mapped to quiescence burden.

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