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LOGIC Tool Effective in Diagnosing MMRD in Tumor & Germline Tissues

2022· article· en· W4312081824 on OpenAlexaboutno aff
Dibash Kumar Das

Bibliographic record

VenueOncology Times · 2022
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsnot available
Fundersnot available
KeywordsMicrosatellite instabilityGermlineDNA mismatch repairCancerGenome instabilityIndelGermline mutationGenetic testingMedicineBiologyComputational biologyGeneticsCancer researchMicrosatelliteBioinformaticsMutationGeneDNAColorectal cancerDNA damage

Abstract

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genetics: geneticsMismatch repair deficiency (MMRD) causes a rapid accumulation of genomic mutations during replication, leading to aggressive cancers that are difficult to treat with conventional chemotherapies. Accurately and efficiently diagnosing somatic and/or germline MMRD is critical for the therapeutic management in patients with the cancer predisposition syndrome known as constitutional mismatch repair deficiency (CMMRD). However, current diagnostic tools are burdensome, expensive, and inconsistent in differentiating true drivers from passenger mutations in MMR genes. Consequently, an affordable and robust tool for MMRD detection in normal and cancer cells is critically needed. In a study conducted on behalf of the International Replication Repair Deficiency Consortium, researchers used a well-annotated dataset of childhood cancers and patients with cancer predisposition syndromes to generate a new tool to detect replication repair deficiency in cancerous and normal tissues. The findings were published in the Journal of Clinical Oncology (2022; doi: 10.1200/JCO.21.02873). It is well-established that that accumulation of microsatellite indels or instability (MSI) is a unique characteristic of MMRD cancers and has traditionally been used to diagnose such tumors. Here, the researchers hypothesized that since the human genome harbors >23 million microsatellites, incorporating a larger number of microsatellites may achiever better sensitivity and specificity. Accordingly, the team developed a low-pass genomic instability characterization (LOGIC) tool which utilizes low-pass whole-genome analysis to identify MSI and diagnose germline MMRD in a large cohort of pediatric cases. To test the efficacy of LOGIC as a diagnostic tool, the researchers compared the novel tools' performance against current clinically approved assays for replication repair deficiency diagnosis, including tumor mutational burden, immunohistochemistry, and the MSI panel. LOGIC was then employed to various normal tissues with CMMRD with thorough clinical data, including age of cancer presentation. The findings revealed that the functional genomic tool performs substantially better than used screening assays. Specifically, LOGIC achieved 100 percent sensitivity and specificity in detecting MMRD in childhood cancers (N=376). LOGIC was more sensitive than tumor mutational burden (80%, P=9.1 × 10−4), immunohistochemistry (86%, P=4.6 × 10−3), or the MSI panel (14%, P=4.3 × 10−12). Moreover, using blood and saliva, LOGIC was able to differentiate CMMRD from other cancer predisposition syndromes (P<.0001, n= 277). Furthermore, increased MMRDness score was linked with younger age of first cancer presentation in individuals with CMMRD (P=2.2 × 10−5). The researchers also noted that, in normal cells, MMRDness scores varied between tissues (GI >blood >brain), increased over time in the same individual, and revealed valuable genotype-phenotype associations between different mutations within the mismatch repair genes. Oncology Times chatted with corresponding study author, Uri Tabori, MD, for additional insights into the study. He is Section Head of Neuro-Oncology in the Division of Hematology/Oncology at The Hospital for Sick Children in Toronto. He participates in the development of systems for early detection and intervention in individuals determined to be at high risk of developing brain tumors, including those with mismatch repair genes. Oncology Times: Why is the diagnosis of mismatch repair deficiency (MMRD) so critical for tumor management? What are the current methodologies used to diagnosis MMRD? Tabori: “MMRD may be somatic (in the tumor only) or in every cell of the patient's body, leading to a rare but aggressive cancer predisposition syndrome known as constitutional MMRD syndrome (CMMRD). LOGIC can detect MMRD in both tumor and normal (non-tumor) tissues, like blood or saliva. The diagnosis of MMRD in a tumor is crucial for treatment, as these tumors are resistant to the established chemoradiation-based therapies. They instead respond well to a novel form of therapy called immune checkpoint inhibitors, which have shown remarkable effects in reducing the tumor volume and improving survival in individuals with MMRD cancers.Uri Tabori, MD: Uri Tabori, MD“Diagnosis of the germline syndrome, CMMRD, by screening normal tissues is critical to patient management, as these individuals are predisposed to developing a multitude of cancer types in childhood. It also allows clinicians to follow an established surveillance protocol to potentially catch cancers early when they can be easily and less aggressively managed. Until now, there are no functional assays to determine constitutional MMRD in normal tissues such as blood. “The current methodologies used to diagnosis MMRD in cancer include microsatellite instability (MSI) testing (which is only 15% sensitive in childhood cancer), immunohistochemistry (which is 80-85% sensitive), and tumor sequencing for tumor mutational burden (which has similar sensitivity but is extremely expensive).” Oncology Times: Based on the study findings, what are the advantages of the LOGIC assay over current established tests when it comes to diagnosing somatic and/or germline MMRD? Tabori: “Altogether, current tools are less robust and expensive. LOGIC is an inexpensive, sensitive, and specific assay to detect MMRD in both tumor and in the germline, shown in our study to display 100 percent specificity and sensitivity. The advantages include a robust rapid, high-throughput assay that can be done on paraffin blocks and on all types of normal samples, including buccal swabs, with high accuracy and potential feasibility in most countries including low- and middle-income countries. Globally, this could be a single assay to replace several cascade assays and at a lower cost. This saves several steps in the diagnosis of MMRD in cancer and germline, which can save time and significant funds per patient. “LOGIC can also simplify the diagnostic workflow with [fewer] steps compared to current established tests for MMRD diagnosis, and with the ability to analyze both tumor and germline tissues without the need for a matched sample (or control). It also costs about $100 per sample—about one-tenth the price of other testing, in which one sample can cost over $1,000 to test. This enables LOGIC to be a tool that can be widely adopted in centers globally, including low- and middle-income countries. It can also be utilized as a screening tool for MMRD, which is not possible with other established tools due to cost and turnaround time. This makes LOGIC a unique tool that can enable us to better understand how prevalent MMRD really is in the general population and investigate more ways to better treat and manage these patients.” Oncology Times: What are some of the biologic and clinical implications of the LOGIC assay to further quantify the extent of microsatellite instability in normal tissues? Tabori: “The clinical implications are quite straightforward. We observed that normal gastrointestinal tissues have a higher level of microsatellite instability than other tissues, making it a good candidate for biopsy in individuals where the diagnosis cannot be clearly made. Additionally, we have been using other normal tissues that are less invasive to make the assay more accessible in low- and middle-income countries and for children, such as taking saliva samples and using LOGIC to determine their microsatellite instability levels. Biologically, we can determine the correlation of tissue cell renewal and microsatellite mutations, which have been shown to be related using models, but we can show it in real human tissues. Also, as for the basis of LOGIC, we observed that tissues without mismatch repair actually acquire variations that are characteristic/unique, as in there are patterns of these variations that can be identified. Using these patterns, which we call mutational signatures, we have been able to parse out how different mechanisms can result in different microsatellite variations, which can imply that there is a determinable biological process that controls the repair process of these regions.” Oncology Times: In terms of next steps for the LOGIC assay, what additional questions are you looking forward to investigating? Tabori: “We are currently working with major centers in Ontario to validate our LOGIC tool for clinical use. We are looking to not only identify MMRD in pediatric samples, but in adulthood cases as well. We are also incorporating other variation signatures that can be inferred from the low-pass whole genome sequencing so that our tool not only captures MMRD, but also other cancer driver mutations and mechanisms. Overall, we are looking forward to expanding LOGIC to be used to diagnose and characterize a wide variety of cancer types to deliver the right type of therapy and cancer management to patients. As the low-pass genome can detect copy number alterations and mutational burden, LOGIC can be expanded to other aspects of cancer management on top of MMRD detection.” Dibash Kumar Das is a contributing writer.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.339
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2022
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