On April 11, 2023 Lunit reported that New findings demonstrate important progress in the development of novel diagnostics for immunotherapy among other important cancer therapies (Press release, Lunit, APR 11, 2023, View Source [SID1234629967]). Lunit will deliver five poster presentations featuring its AI-biomarker platform, Lunit SCOPE IO, at the annual meeting to be held in Orlando, Florida, on April 14-19.

Schedule your 30 min Free 1stOncology Demo!
Discover why more than 1,500 members use 1stOncology™ to excel in:

Early/Late Stage Pipeline Development - Target Scouting - Clinical Biomarkers - Indication Selection & Expansion - BD&L Contacts - Conference Reports - Combinatorial Drug Settings - Companion Diagnostics - Drug Repositioning - First-in-class Analysis - Competitive Analysis - Deals & Licensing

                  Schedule Your 30 min Free Demo!

One of the studies to be presented evaluates a deep learning-based ensemble model to predict the KRAS G12C mutation, most common among KRAS gene mutations, which accounts for 25% of non-small cell lung cancer patients. Employing the AI model developed using samples from The Cancer Genome Atlas LUAD and LUSC (TCGA-Lung), researchers conducted a novel approach to improve the performance of KRAS G12C prediction.

According to the research, the prediction model showed improved accuracy compared to previously reported KRAS mutation prediction studies. The Lunit SCOPE based KRAS G12C mutation prediction model showed a high predictive power with an AUC (Area Under the Curve) of 0.787, indicating the accuracy of the AI algorithm. It also showed AUC of 0.745 in validation with independent external data.

"As the KRAS G12C mutation has become targetable in NSCLC, tissue-based KRAS mutation tests are now an essential practice for treatment decisions," explained Chan-Young Ock, Chief Medical Officer at Lunit. "By combining simple H&E analysis model with Lunit SCOPE IO’s in-depth predictive features, our novel approach showed significant improvement in prediction. In the future, we believe that such a model will be able to provide predictive results before applying molecular testing, which is relatively time-consuming and expensive, and may help enable rapid treatment decisions."

Another study demonstrates the effectiveness of Universal immunohistochemistry (UIHC), an AI-powered image analyzer, in detecting and quantifying untrained new targets of interest expressed in multiple cancer types. The AI model was trained on the dataset of PD-L1 and HER2 stained lung, bladder, and breast cancer slides, and evaluated on its performance on the hold-out IHC dataset of untrained target and cancer types. Compared to the AI models trained with a single IHC and cancer type, UIHC showed superior performance for new IHC and cancer types. Researchers concluded that UIHC model will be a useful tool for the future clinical research targeting novel tumor-associated antigens.

Other studies to be presented further demonstrate the effectiveness of Lunit SCOPE IO as a diagnostic aid in the treatment of various cancer types.

Lunit SCOPE IO analyzes a patient’s cancer tissue slide image by observing the distribution of tumor-infiltrating lymphocytes (TIL)—one of the immunocytes that fight cancer cells. Based on the spatial distribution pattern of TILs and cancer cells in the tumor microenvironment, Lunit SCOPE IO identifies the tissue sample as one of three immune phenotypes (IP): inflamed, immune-excluded, or immune-desert.

In one study assessing Lunit SCOPE IO as a predictive biomarker for anti-PD-1 therapy in advanced biliary tract cancer (BTC), researchers conducted a retrospective analysis of the relationship between the clinical outcomes and TIL using the AI solution. After analysis of pre-treatment whole slide images and clinical outcomes, patients with the inflamed IP had favorable clinical outcomes after anti-PD-1 therapy than other phenotype groups, showing that immune phenotypes as classified by Lunit SCOPE IO could be an effective biomarker to predict the clinical outcomes of patients with advanced BTC.

Other studies include an analysis of the distribution of TILs and associated genomic signatures based on proximity to the tumor-stromal border (TSB) in the TCGA pan-carcinoma dataset, as well as an application of Lunit SCOPE IO in the TCGA ovarian cancer dataset demonstrating the enrichment of inflammatory immune and transcriptomic traits in the Inflamed IP classified by the AI solution.

"We are excited to bring new research using Lunit SCOPE in more cancer types and treatment settings," said Brandon Suh, CEO of Lunit. "Lunit will continue to enable novel academic research and innovative product development to provide the most appropriate treatment for cancer patients."

Visit the Lunit team at Booth 2671. Reach out to schedule a meeting at ([email protected]).

Lunit’s Abstracts at AACR (Free AACR Whitepaper) 2023

1. 5399 / 15 – Deep learning-based ensemble model using H&E images for the prediction of KRAS G12C mutations in non-small cell lung cancer

2. 5392 / 8 – Universal immunohistochemistry positivity classification of cancer cells across multiple cancer types and antibodies using artificial intelligence

3. 4333 / 8 – Spatial analysis of tumor-infiltrating lymphocytes in tumor microenvironment as biomarker for immune checkpoint inhibition in biliary tract cancer

4. 5389 / 5 – Micron-resolution spatial analysis near the tumor-stromal border reveals a distinct density distribution of tumor-infiltrating lymphocytes and related genomic features

5. 5446 / 29 – Immune phenotypes classified by deep learning-based H&E tissue analyzer demonstrate distinct immune landscape and transcriptomic features in ovarian cancer

On April 11, 2023 Virtuoso Therapeutics, Inc., a private oncology-focused company developing novel bispecific antibodies reported that it will present three posters highlighting the preclinical data from leading bispecific antibody and ADC programs at the American Associate for Cancer Research (AACR) (Free AACR Whitepaper) 2023 Annual Meeting (Press release, Virtuoso Therapeutics, APR 11, 2023, View Source [SID1234629966]).

Schedule your 30 min Free 1stOncology Demo!
Discover why more than 1,500 members use 1stOncology™ to excel in:

Early/Late Stage Pipeline Development - Target Scouting - Clinical Biomarkers - Indication Selection & Expansion - BD&L Contacts - Conference Reports - Combinatorial Drug Settings - Companion Diagnostics - Drug Repositioning - First-in-class Analysis - Competitive Analysis - Deals & Licensing

                  Schedule Your 30 min Free Demo!

The details of the Company’s presentations at the AACR (Free AACR Whitepaper) are as follows:

Poster Presentation #1870:

Title: VBI–003, a CD47xEpCAM bispecific antibody as a potential treatment for colorectal and small cell lung cancers
Session Category: Immunology
Session Title: Therapeutic Antibodies 1
Presenting Author: Oi Kwan Wong, Ph.D., Senior Director, Translational Biology
Date/Time: April 17th 9:00AM-12:30PM
Location: Section 25

Poster Presentation #6334:

Title: VBI-002, a CD47xICAM-1 bispecific antibody for the treatment of hepatocellular carcinoma, melanoma and non-small cell lung cancers
Session Category: Immunology
Session Title: Anticancer Immunotherapeutics
Presenting Author: Oi Kwan Wong, Ph.D., Senior Director, Translational Biology
Date/Time: April 19th 9:00AM-12:30PM
Location: Section 22

Poster Presentation #6298:

Title: A novel topoisomerase I inhibitor based anti-ICAM–1 antibody drug conjugate for the treatment of hematologic malignancies and solid tumors
Session Category: Experimental and Molecular Therapeutics
Session Title: Growth Factor Receptors as Therapeutic Targets
Presenting Author: Oi Kwan Wong, Ph.D., Senior Director, Translational Biology
Date/Time: April 19th 9:00AM-12:30PM
Location: Section 21

"We believe that our best-in-class CD47 bispecific antibodies confer greater tumor selectivity without sacrificing potency and efficacy. They have been optimized and are ready to begin IND enabling studies," said Sofie Qiao, PhD, President and CEO of Virtuoso Therapeutics. Posters will be available at www.virtuosotherapuetics.com after the meeting.

On April 11, 2023 Strata Oncology, Inc. ("Strata"), a next-generation precision oncology company enabling smarter and earlier cancer treatment, reported that it will present new data in four scientific posters at the American Association for Cancer Research (AACR) (Free AACR Whitepaper) Annual Meeting 2023, taking place April 14-19, 2023 in Orlando, Florida (Press release, Strata Oncology, APR 11, 2023, View Source [SID1234629965]).

Schedule your 30 min Free 1stOncology Demo!
Discover why more than 1,500 members use 1stOncology™ to excel in:

Early/Late Stage Pipeline Development - Target Scouting - Clinical Biomarkers - Indication Selection & Expansion - BD&L Contacts - Conference Reports - Combinatorial Drug Settings - Companion Diagnostics - Drug Repositioning - First-in-class Analysis - Competitive Analysis - Deals & Licensing

                  Schedule Your 30 min Free Demo!

The data to be presented includes results for innovative, proprietary predictive biomarkers for fam-trastuzumab-deruxtecan-nxki, sacituzumab govitecan and pembrolizumab. Strata has developed these biomarkers and others using data collected through an observational clinical trial protocol called the Strata Trial (NCT03061305). All of these biomarkers take advantage of the company’s unique molecular profiling platform that combines DNA and quantitative RNA sequencing on a single small tumor tissue sample.

Strata Oncology to present new data in four scientific posters at the AACR (Free AACR Whitepaper) Annual Meeting, taking place April 14 – 19.

"Strata Oncology is leading the way in bringing expression-based therapies, such as antibody-drug conjugates and immunotherapies, into the precision era with highly quantitative RNA and multivariate predictive treatment selection algorithms," said Scott Tomlins, M.D., Ph.D., Strata Oncology co-founder and chief medical officer. "Data from the Strata Trial is allowing us to identify new biomarker-guided patient populations for therapies already on the market, thus opening up treatment pathways that can drive better outcomes for more people. We look forward to sharing our latest advances at the AACR (Free AACR Whitepaper) meeting."

Poster presentation details:

Poster Title: 968/19 – Evaluation of Her2 RNA expression as a potential predictive biomarker for anti-Her2 therapy
Track: Biomarkers of Therapeutic Benefit 1
Session Date and Time: Sunday Apr 16, 2023, 1:30 PM – 5:00 PM EDT
Overview: Trastuzumab-deruxtecan is effective in "HER2 Low" (1+ or 2+ expression by immunohistochemistry (IHC)) breast cancer. There is increasing interest in defining a sub-population of IHC 0+ tumors that may have HER2 expression below the limit of IHC detection/quantification and may thus also be responsive. Using data from its high dynamic range assay for HER2 expression and clinical outcome data from the Strata Trial, Strata defined a HER2 RNA low threshold based on IHC from breast cancer patients. At this threshold, nearly half of 0+ breast cancers were classified as HER2 RNA Low, as were more than a quarter of non-breast solid tumors, representing tumors that may be responsive to anti-HER2 therapies. HER2 RNA Low has the potential to be an alternative biomarker to Her2 IHC Low, with the opportunity to further expand trastuzumab-deruxtecan use.

Poster Title: 2171 /13 – A multivariate biomarker predicts sacituzumab govitecan response in solid tumors
Track: Biomarkers of Therapeutic Benefit 3
Session Date and Time: Monday Apr 17, 2023, 9:00 AM – 12:30 PM EDT
Overview: Despite the recent clinical success of antibody drug conjugates (ADCs), such as the TROP2-targeted ADC sacituzumab govitecan (SG), predictive biomarkers for these therapies are lacking. Leveraging DNA and RNA sequencing data and clinical outcomes data from the Strata Trial, Strata developed a multivariate biomarker algorithm, which combines TROP2 and proliferation by gene expression with tumor cellularity, that produced biomarker positive rates correlating with the objective response rates observed for SG in the IMMU-12-01 basket trial. The multivariate biomarker accounts for 67% of the variability observed in SG response rates and may thus identify patients likely to benefit from SG. Interestingly, most tumor types had biomarker positive rates >5%, suggesting the potential for a tumor type-agnostic approach to patient selection. The biomarker has the potential to improve the selection of patients who are more likely to benefit from SG and may be generalizable to other ADCs.

Poster Title: CT059 / 17 – StrataPATH: a multicohort, non-randomized, open-label phase 2 trial to explore efficacy and safety of FDA-approved cancer therapies in novel biomarker-guided patient population
Track: Phase II and Phase III Clinical Trials in Progress
Session Date and Time: Monday Apr 17, 2023, 9:00 AM – 12:30 PM EDT
Overview: The Strata Precision Indications for Approved Therapies (Strata PATH; NCT05097599) trial is a non-randomized open-label, prospective pan-tumor therapeutic trial designed to evaluate the efficacy and safety of multiple FDA-approved cancer therapies in new, biomarker-guided patient populations. Enrollment into a cohort of this basket trial is based on novel biomarkers including DNA, quantitative RNA expression and novel multivariate algorithms that account for both tumor and tumor microenvironment variables hypothesized to predict improved therapeutic response. The therapeutic classes evaluated in Strata PATH include targeted therapies, antibody-drug conjugates, immunotherapies, and angiogenesis inhibitors. Strata PATH provides the next important step forward in precision medicine, guiding clinical trial and therapy selection by expanding biomarker testing to quantifiable RNA expression and multivariant algorithm based molecular testing.

Poster Title: 4348 / 23 – Validation of an integrative pan-solid tumor predictor of pembrolizumab monotherapy benefit
Track: Biomarkers of Therapeutic Benefit 4
Session Date and Time: Tuesday Apr 18, 2023, 9:00 AM – 12:30 PM EDT
Overview: Strata previously reported the development and validation of an integrative Immunotherapy Response Score (IRS) algorithm, which integrates tumor mutation burden (TMB) and quantitative gene expression of tumor and tumor microenvironment biomarkers to predict anti-PD-1 or PD-L1 (together anti-PD-[L]1) monotherapy benefit across solid tumors from routine formalin fixed paraffin embedded samples. Strata has now evaluated IRS performance for predicting immunotherapy benefit in a second, independent validation cohort of patients treated with pembrolizumab monotherapy. As seen before, pembrolizumab monotherapy real-world progression-free survival (rwPFS) was significantly longer in IRS-high vs. IRS-low patients. In a case cross-over analysis of patients treated with systemic therapy prior to pembrolizumab monotherapy, pembrolizumab rwPFS was significantly longer than preceding therapy in IRS-high patients but not IRS-low patients. These results confirm the pan-solid tumor PD-(L)1 monotherapy predictive nature of the IRS biomarker.

On April 11, 2023 PathAI, a leading provider of AI-powered pathology tools to advance precision medicine, reported their recent research will be presented at the American Association for Cancer Research (AACR) (Free AACR Whitepaper) Annual Meeting 2023, which will be held in Orlando, FL from April 14-19, 2023 (Press release, PathAI, APR 11, 2023, View Source [SID1234629964]). PathAI will share three posters that highlight uses and advantages of AI-based methods to identify and examine non-small cell lung cancer (NSCLC) and renal cell carcinoma (RCC) specimens. Additionally, PathAI collaborated with Genentech, a member of the Roche Group, on two submissions, an oral presentation on H&E-based digital pathology biomarkers in metastatic NSCLC, and a poster presentation on digital PD-L1 tumor cell scoring in NSCLC. PathAI will also be exhibiting in booth 315, where it will showcase the capabilities of its newly launched PathExplore product, its AI-powered panel of histopathology features that spatially characterize the tumor microenvironment (TME) with single-cell resolution from H&E slide images.

Schedule your 30 min Free 1stOncology Demo!
Discover why more than 1,500 members use 1stOncology™ to excel in:

Early/Late Stage Pipeline Development - Target Scouting - Clinical Biomarkers - Indication Selection & Expansion - BD&L Contacts - Conference Reports - Combinatorial Drug Settings - Companion Diagnostics - Drug Repositioning - First-in-class Analysis - Competitive Analysis - Deals & Licensing

                  Schedule Your 30 min Free Demo!

"Our research demonstrates forward momentum in utilizing machine learning, cell segmentation models, and image analysis at scale to better recognize and analyze tissue morphology at the cellular level, revealing new biomarkers and predictive links to targeted therapies," said Mike Montalto, Ph.D., chief scientific officer at PathAI. "With this body of research, we are another step closer to improving oncology drug development and outcomes for these difficult to treat cancers."

PathAI collaborator Genentech will give an oral presentation, "Digital pathology-based prognostic and predictive biomarkers in metastatic non-small cell lung cancer," highlighting the relationship between the tumor microenvironment (TME) and patient response to targeted cancer immunotherapy by applying machine learning algorithms to study the TME in metastatic NSCLC. By quantifying digital pathology cell and region features, and using feature variability as a discovery tool, the study identified a feature set associated with outcome to PD-L1 targeted therapy, illustrating how novel data modalities can be integrated to elucidate biomarkers of immunotherapy response.

In a poster presentation in partnership with Genentech, "Digital SP263 PD-L1 tumor cell scoring in NSCLC achieves comparable outcome prediction to manual pathology scoring," the companies will demonstrate the effectiveness of an AI-based model for PD-L1 quantification in predicting NSCLC outcomes compared to manual scoring.

In a poster on renal cell carcinoma, "Machine learning models identify key histological features of renal cell carcinoma subtypes," PathAI will explain how their machine learning model quantified the RCC environment, allowing identification of spatially specific differences that correlate with histological subtypes, mutations and vascularization.

The full list of PathAI’s research submissions is listed below. More information on each research abstract can be found here.

Oral Presentation: Digital pathology based prognostic and predictive biomarkers in metastatic NSCLC

Session MS.CL01.02 – Immune-based Biomarkers for Prognostic and Predictive Benefit

Abstract presentation number: 5705

Session time: April 18, 2023, 2:30 PM – 4:30 PM

Presentation time: 3:37 PM – 3:52 PM

Collaborator: Genentech

Poster Presentation: Digital SP263 PD-L1 tumor cell scoring in non-small cell lung cancer achieves comparable outcome prediction to manual pathology scoring

Session PO.BCS01.02 – Artificial Intelligence and Machine/Deep Learning 1

Abstract presentation number: 5358 / 7

Poster hours: April 18, 2023, 1:30 PM – 5:00 PM

Collaborator: Genentech

Poster Presentation: Machine learning models identify key histological features of renal cell carcinoma subtypes

Session PO.BCS02.03 – Artificial Intelligence: From Pathomics to Radiomics

Abstract presentation number: 5422 / 5

Poster hours: April 18, 2023, 1:30 PM – 5:00 PM

Poster Presentation: Artificial intelligence (AI)-based classification of stromal subtypes reveals associations between stromal composition and prognosis in NSCLC

Session PO.BCS02.03 – Artificial Intelligence: From Pathomics to Radiomics

Abstract presentation number: 5447 / 30

Poster hours: April 18, 2023, 1:30 PM – 5:00 PM

Poster Presentation: Development of a high-throughput image processing pipeline for multiplex immunofluorescence whole slide images at scale

Session PO.BCS02.02 – Integrative Spatial and Temporal Multi-omics of Cancer

Abstract presentation number: 6616 / 21

Poster hours: April 19, 2023, 9:00 AM – 12:30 PM

On April 11, 2023 Independent biopharmaceutical company Specialised Therapeutics Asia Pte Ltd (ST) reported that it will partner with CTTQ-Akeso (Shanghai) Biomed. Tech. Co., Ltd. (CTTQ-Akeso)（jointly established by Akeso, Inc. (9926.HK, Akeso) and Chia Tai Tianqing Pharmaceutical Group Co., Ltd. to commercialise a new immuno-oncology therapy in Australia, Singapore and across Southeast Asia (Press release, Specialised Therapeutics Asia, APR 11, 2023, View Source [SID1234629963]).

Schedule your 30 min Free 1stOncology Demo!
Discover why more than 1,500 members use 1stOncology™ to excel in:

Early/Late Stage Pipeline Development - Target Scouting - Clinical Biomarkers - Indication Selection & Expansion - BD&L Contacts - Conference Reports - Combinatorial Drug Settings - Companion Diagnostics - Drug Repositioning - First-in-class Analysis - Competitive Analysis - Deals & Licensing

                  Schedule Your 30 min Free Demo!

The therapy ANNIKO (penpulimab) is an anti-PD1 monoclonal antibody currently under regulatory review by the US FDA for nasopharyngeal carcinoma – a difficult to treat form of head and neck cancer.

This follows the FDA granting ANNIKO orphan drug and fast track designations in 2020, as well as a further "breakthrough therapy" designation in March 2021. In addition, ANNIKO was granted a FDA Real-Time Oncology Review (RTOR) in 2021, to accelerate the drug approval process.[1,2]

ANNIKO has been approved in China for the treatment of adult patients with relapsed or refractory classical Hodgkin’s lymphoma (advanced r/r cHL) who have undergone at least second-line chemotherapy, as well as first-line treatment of locally advanced or metastatic squamous non-small cell lung cancer (sq-NSCLC) in combination with chemotherapy.[3]

Under the terms of the arrangement, ST will be responsible for all marketing, regulatory and distribution activities in its key regions of Australia, Singapore and across Southeast Asia.

CTTQ-Akeso retains the rights of conducting any development work in relation to ANNIKO and Akeso retains all rights to product manufacture and supply.

Announcing the partnership, ST Chief Executive Officer Carlo Montagner said ANNIKO was the first immuno-oncology drug to be included in the company’s therapeutic portfolio and the arrangement was further endorsement of ST’s regional capabilities.

"ANNIKO will provide a new opportunity for patients in our regions with nasopharyngeal carcinoma – a very difficult to treat cancer – to be treated with an immune-based therapy," he said.

"Nasopharyngeal carcinoma is native to Southeast Asia, affecting between 15 and 50 people in every 100,000[4] and with almost 37,000 new cases diagnosed annually in this region.[5] Making ANNIKO available for this disease is a high priority."

Akeso CEO Michelle Xia said the company looked forward to collaborating with ST and providing eligible cancer patients with world-class therapy.

"We trust that ST’s expertise in these regions, navigating complex regulatory channels will ensure our therapy reaches as many eligible patients as possible," she said.

"We look forward to a successful and mutually beneficial partnership, working together with a shared goal of improving patient outcomes."

Regulatory activities are currently in progress.