Mark J. Ratain’s research while affiliated with University of Chicago and other places

This Viewpoint reviews the accelerated approval process and lack of postapproval studies to verify its benefit as it applied to sotorasib, a treatment for non–small cell lung cancer with the KRAS g12c mutation, and recommends measures to ensure confirmatory follow-up studies.

Background Gene signatures derived from transcriptomic-causal networks offer potential for tailoring clinical care in cancer treatment by identifying predictive and prognostic biomarkers. This study aimed to uncover such signatures in metastatic colorectal cancer (CRC) patients to aid treatment decisions. Methods We constructed transcriptomic-causal networks and integrated gene interconnectivity into overall survival (OS) analysis to control for confounding genes. This integrative approach involved germline genotype and tumor RNA-seq data from 1165 metastatic CRC patients. The patients were enrolled in a randomized clinical trial receiving either cetuximab or bevacizumab in combination with chemotherapy. An external cohort of paired CRC normal and tumor samples, along with protein-protein interaction databases, was used for replication. Results We identify promising predictive and prognostic gene signatures from pre-treatment gene expression profiles. Our study discerns sets of genes, each forming a signature that collectively contribute to define patient subgroups with different prognosis and response to the therapies. Using an external cohort, we show that the genes influencing OS within the signatures, such as FANCI and PRC1, are upregulated in CRC tumor vs. normal tissue. These signatures are highly associated with immune features, including macrophages, cytotoxicity, and wound healing. Furthermore, the corresponding proteins encoded by the genes within the signatures interact with each other and are functionally related. Conclusions This study underscores the utility of gene signatures derived from transcriptomic-causal networks in patient stratification for effective therapies. The interpretability of the findings, supported by replication, highlights the potential of these signatures to identify patients likely to benefit from cetuximab or bevacizumab.

Background Cancer patients frequently suffer from pain, often managed with opioids. However, undertreated pain remains a significant concern. Opioid effectiveness varies due to genetic differences in how individuals metabolize some of these medications. While prior research suggests promise in tailoring opioid prescriptions based on CYP2D6 genetic makeup, its application in cancer pain management remains limited. This study investigates the potential benefits of preemptive CYP2D6 genotyping for cancer patients initiating opioid therapy, focusing on codeine, tramadol, and hydrocodone, whose efficacy is demonstrably impacted by CYP2D6 variations. Methods This is a randomized, prospective study to evaluate the effects of preemptive pharmacogenomic (PGx) testing on opioid dosing decisions/selections and composite pain score in oncology patients. Patients with metastatic solid tumors for whom near-future opioid therapy is anticipated will be randomized to PGx and control arms, stratified by the presence or absence of bony metastases and history of opioid use. In the PGx arm, patients will be preemptively tested using a panel of pharmacogenomic genetic variants, and providers will receive opioid dosing guidance via an electronic medical record-embedded clinical decision support tool. In the control arm, pain prescribing will occur per standard of care without genotype information. Planned Outcome The primary study outcome will be composite pain intensity during the first 45 days after an index opioid prescription for codeine, tramadol, or hydrocodone. Safety will be assessed by comparing opioid-related adverse event rates between the two study arms. Secondary outcomes will include rates of hospitalization/emergency room visits, cumulative morphine equivalents received, and type of first opioid prescribed.

Introduction Acute chest syndrome (ACS) is a life-threatening complication of sickle cell disease (SCD). ACS severity is inconsistently defined, typically using either the number of involved lung lobes on chest imaging with possible delays in chest imaging changes or the level of transfusion support, which can be subjectively applied. Additionally, the clinical course of ACS is difficult to predict. Thus, we evaluated the utility of the ratio of the peripheral oxygen saturation obtained from pulse oximetry to the fraction of inspired oxygen (SaO2/FiO2) in defining ACS severity and associations with clinical outcomes. Methods This retrospective observational study included all ACS admissions of patients 18 years or older with SCD at a single health center from January 1, 2017 to December 31, 2021. ACS was defined as having at least one symptom (fever, chest pain, hypoxemia, cough, wheezing, or shortness of breath) and a new opacity on chest radiography. Clinical and oxygenation data were collected via manual chart review. Arterial oxygen saturation (SaO2) was approximated by the pulse oximetry (SpO2) measurement recorded in the electronic medical record flowsheets. Every SpO2 measurement from presentation in the ED until the first 96 hours after ACS diagnosis was recorded. FiO2 was calculated based on the type of oxygen support. We stratified admissions by home oxygen support given the impact of supplemental oxygen on the SaO2/FiO2 ratio. We compared the SaO2/FiO2 ratio to two existing methods of defining ACS severity in the literature: 1) the number of opacified lobes on chest radiography (1-2 versus 3+ lobes) and 2) the type of transfusions (simple versus red cell exchange [RCE]). We also compared the SaO2/FiO2 ratio to the clinical outcome of intensive care unit (ICU) transfer, which was equivalent to the composite endpoint of ICU transfer or death. Three key timepoints were determined in the patient's clinical course for determining the utility of triaging a patient based on their current SaO2/FiO2 ratio: 1) presentation in the emergency department (ED), 2) initiation of antibiotics for ACS, and 3) chest radiography confirmation of ACS diagnosis. Analyses were stratified by whether patients used home oxygen or not. Results Of the 227 ACS admissions during the study period, 54% were female, the mean age at admission was 28.9 years (SD 9.7), and 70% had Hgb SS. Admissions with an ICU transfer had a lower hemoglobin and platelet count at ACS diagnosis than those that remained on the floor (Hgb 7.3 vs 7.7 g/dL, p=0.03; platelet 303,000/µL vs 376,000/µL, p=0.01). Of the 227 admissions, 32 admissions (14%) were severe based on having 3+ lobes with opacities on chest radiography, and 45 admissions (20%) were severe due to receiving RCE. Home oxygen use was documented for 43 (19%) admissions. For admissions without home oxygen, chest imaging with 3+ opacified lobes had lower SaO2/FiO2 than those with 1-2 lobes (322 vs 383, p=0.006), and RCE was associated with lower SaO2/FiO2 than no RCE (293 vs 414, p<0.001). Similarly, admissions with home oxygen had lower SaO2/FiO2 when RCE was used (254 vs 303, p=0.007). For the 3 key timepoints regardless of home oxygen status, SaO2/FiO2 ratio did not correlate with subsequent ICU transfer at ED presentation (AUC 0.59), but it did correlate strongly at antibiotic initiation (AUC 0.78) and at ACS diagnosis (AUC 0.76). Thus, SaO2/FiO2 ratio cutoffs of 314 (sensitivity 54%, specificity 85%) for patients without home oxygen and 276 (sensitivity 65%, specificity 85%) for patients with home oxygen were calculated for triaging whether patients would transfer to the ICU or not. These cutoffs were highly associated with ICU transfer in multivariable multilevel models (314: aOR 12.2, 95% CI 2.9-51.6; 276: aOR 6.9, 95% CI 1.7-28.6). Conclusions The SaO2/FiO2 ratio is associated with ACS severity and clinical outcomes in hospitalized patients with SCD and warrants further evaluation. The recommended SaO2/FiO2 ratio cutoff of 314 for patients without home oxygen is equivalent to saturation of 91% on 2 L/min nasal cannula, and the recommended SaO2/FiO2 ratio of 276 for patients with home oxygen is equivalent to saturation of 91% on 3 L/min. This bedside measurement of oxygen status may be a clinically useful, inexpensive biomarker for assessing ACS severity and guiding clinical management such as transfer to an ICU. Further study of these cutoffs through a prospective multi-center study is indicated.

Background Herein, we report results from a genome-wide study conducted to identify protein quantitative trait loci (pQTL) for circulating angiogenic and inflammatory protein markers in patients with metastatic colorectal cancer (mCRC). The study was conducted using genotype, protein marker, and baseline clinical and demographic data from CALGB/SWOG 80405 (Alliance), a randomized phase III study designed to assess outcomes of adding VEGF or EGFR inhibitors to systemic chemotherapy in mCRC patients. Germline DNA derived from blood was genotyped on whole-genome array platforms. The abundance of protein markers was quantified using a multiplex enzyme-linked immunosorbent assay from plasma derived from peripheral venous blood collected at baseline. A robust rank-based method was used to assess the statistical significance of each variant and protein pair against a strict genome-wide level. A given pQTL was tested for validation in two external datasets of prostate (CALGB 90401) and pancreatic cancer (CALGB 80303) patients. Bioinformatics analyses were conducted to further establish biological bases for these findings. Results The final analysis was carried out based on data from 540,021 common typed genetic variants and 23 protein markers from 869 genetically estimated European patients with mCRC. Correcting for multiple testing, the analysis discovered a novel cis-pQTL in LINC02869, a long non-coding RNA gene, for circulating TGF-β2 levels (rs11118119; AAF = 0.11; P-value < 1.4e-14). This finding was validated in a cohort of 538 prostate cancer patients from CALGB 90401 (AAF = 0.10, P-value < 3.3e-25). The analysis also validated a cis-pQTL we had previously reported for VEGF-A in advanced pancreatic cancer, and additionally identified trans-pQTLs for VEGF-R3, and cis-pQTLs for CD73. Conclusions This study has provided evidence of a novel cis germline genetic variant that regulates circulating TGF-β2 levels in plasma of patients with advanced mCRC and prostate cancer. Moreover, the validation of previously identified pQTLs for VEGF-A, CD73, and VEGF-R3, potentiates the validity of these associations.