PURPOSE:Time-to-progression ratio (TTPr) measures intra-patient treatment benefit by comparing disease control on study treatment with that of the immediately preceding therapy. Its prognostic validity in the immune checkpoint inhibitor (ICI) era remains uncertain. METHODS:We performed a pooled patient-level analysis of eight phase II trials. Associations between TTPr, TTP on prior therapy (TTP1), and on-study TTP (TTP2/ PFS), objective response rate (ORR), with overall survival (OS) were evaluated using Cox regression. Landmark analyses at 6-months were used to mitigate guarantee-time bias. RESULTS:Among 246 evaluable participants, median TTP1 and TTP2 were 3.9 and 2.1 months, respectively, with poor correlation (r = 0.02). TTPr was not associated with OS (TTPr ≥1.3 vs <1.3, HR 0.85, 95% CI 0.57-1.26). In contrast, TTP2 and ORR were strongly prognostic (TTP2 ≥2.1 months vs <2.1 months: HR 0.51, 95% CI 0.35-0.76, p < 0.001); (response vs non-response: HR 0.19, 95% CI 0.07-0.52, p = 0.001) and remained independently associated with OS in multivariable analyses. Findings were consistent across ICI and non-ICI trials. CONCLUSIONS:TTPr is not a robust prognostic measure in platform trials. Although this raises concern regarding its validity as a surrogate endpoint for OS, formal evaluation requires randomized treatment comparisons.

Advances in genomics have enabled anticancer therapies to be tailored to target specific genomic alterations. Single-arm trials (SATs), including those incorporated within umbrella, basket, and platform trials, are widely adopted when it is not feasible to conduct randomized controlled trials in rare biomarker-defined subpopulations. External controls (ECs), defined as control arm data derived outside the clinical trial, have gained renewed interest as a strategy to supplement evidence generated from SATs to allow comparative analysis. There are increasing examples demonstrating the application of EC in precision oncology trials. The prospective application of EC in conducting comparative studies is associated with distinct methodological challenges, the specific considerations for EC use in biomarker-defined subpopulations have not been adequately discussed, and a formal framework is yet to be established. In this review, we present a framework for conducting a prospective comparative analysis using EC. Key steps are (1) defining the purpose of using EC to address the study question, (2) determining if the external data are fit for purpose, (3) developing a transparent study protocol and a statistical analysis plan, and (iv) interpreting results and drawing conclusions on the basis of a prespecified hypothesis. We specify the considerations required for the biomarker-defined subpopulations, which include (1) specifying the comparator and biomarker status of the comparator group, (2) defining lines of treatment, (3) assessment of the biomarker testing panels used, and (4) assessment of cohort stratification in tumor-agnostic studies. We further discuss novel clinical trial designs and statistical techniques leveraging EC to propose future directions to advance evidence generation and facilitate drug development in precision oncology.

1557 Background: Molecular Tumor Boards (MTB) have become the standard for deriving consensus therapy (Rx) recommendations (rec) for patients (pts) with advanced cancer undergoing comprehensive genomic profiling (CGP). However, finding matched Rx and trial options remains laborious, needing informatics strategies. Methods: We examined the outcomes before and after implementation of a decision support system (DSS) at the MTB of the Australian Molecular Screening & Therapeutics program (MoST, ACTRN12616000908437), enrolling pts with refractory solid tumors and linking CGP results to Rx and trials through rec on clinical reports. The DSS comprises a variant interpretation pipeline, a symbolic AI system integrating the TOPOGRAPH database and an annotated trials registry, and a web platform used by the MTB for producing reports shortlisting matching Rx and therapeutic trials. The primary endpoint is the cumulative participation rate (CPR) in genomic matched trials (excluding MoST-related trials) in pts who received Rx after CGP. The secondary endpoints are the CPR in any trial, and overall survival (OS) from MTB. The Fine-Gray model was used to estimate the subdistribution hazard ratios (sHR) for between-group differences in participation. Kaplan-Meier and Cox regression were used for OS analysis. The time-to-event analyses were adjusted for age, ECOG, cancer type, lines of prior rx, and lead-time bias (OS only). Results: In 2203 of 5186 pts (42.5%) received ≥ 1 Rx after CGP, 971 pts were reviewed at MTB before and 1272 after DSS implementation in Sep 2020. At 3, 6 and 12 months (m) after enrolment, CPR in matched trials were 3.2%, 5.0%, and 6.8% before implementation and 3.6%, 5.8%, and 8.9% afterwards (sHR 1.19, 95% CI 0.90–1.57, p=0.23). Pts who received an MTB rec were more likely to participate in a matched trial (sHR 4.75, 3.13–7.23, p<0.001). Notably, DSS specifically increased the likelihood of trial participation following MTB rec (interaction sHR 2.69, 1.02–7.07, p=0.045), with 12m CPR increasing from 10.0% to 12.2% after implementation of the DSS in pts with a MTB rec, whilst for pts without a MTB rec, the CPR fell from 3.1% to 1.6% after implementation. No association was seen between participation in any trials and MTB recs (sHR 1.12, 0.95–1.32) or implementation (sHR 0.95, 0.81–1.11; CPR pre 21.6% v post 23.7% at 12m). No OS difference was seen comparing before with after implementation of the DSS (median 16.7 v 15.3m, adjusted HR 0.97, 0.87–1.08). However, pts receiving genomic matched Rx had a longer OS (median 20.1 v 15.0m unmatched, HR 0.76, p=0.002). Conclusions: The observed interaction between the implementation of DSS and MTB rec suggests there is effect modification in participation rates of pts in genomic matched trials, warranting exploration into how AI might enhance trial participation among pts with incurable cancers undergoing CGP.

105 Background: Tumor molecular profiling (TMP) provides an opportunity to identify heritable cancer predisposition. Molecular Screening and Therapeutics Study (MoST) (8000 patients, 2016-23) and Cancer Screening Program (CaSP) (23000 patients, 2023-25) are Australian research programs providing TMP for therapy matching in advanced cancer. Matched germline testing is resource-inefficient and is not performed . An integrated approach between TMP and cancer genetics is needed to improve familial cancer outcomes through prevention and early detection. Methods: In MoST, potential germline variants (PGV) in actionable cancer genes were investigated in blood DNA in a research setting. Positive cases were informed, and a genetics review for clinical testing recommended. In CaSP, germline follow-up recommendations are included in the Molecular Oncology Board (MOB) Report based on decision algorithms to inform clinicians of PGV needing clinical assessment. Cancer genetics clinics in Australia were surveyed regarding preferences for the return of genetic information from tumor profiling. A centralised precision care clinic was launched in March 2024 to investigate the implementation of returning PGV information from tumor-only profiling. Results: In MoST, 38% (140/367) of PGVs tested were positive in blood DNA. Of these, 44% were identified in the highest actionability genes: BRCA1, BRCA2, PALB2, Lynch Syndrome. The validation and return of results process was unsatisfactory; it was resource-heavy, timeframes were extended, DNA was sometimes unavailable, and communicating information to non-participating relatives of deceased participants was challenging due to a lack of established pathways. The systems design in CaSP has allowed the study to manage higher volume without a net increase in germline workforce. To date, 2372 patients have completed profiling with 173 MOB recommendations for PGV validations. Fifty-four cancer genetics staff nationally responded to the survey. Many (61%) were concerned about the increased uptake of TMP without a workforce to match germline testing demand (97%) and lack of funding assigned in a universal healthcare system (70%) being main concerns. Most (82%) supported a centralised service anticipating improved efficiency gain (71%), equity of access (77%) and streamlining of processes (71%). The stakeholders voiced a consistently high (>50%) demand for information regarding PGV in lower actionability genes. MOB recommendations were adapted to reflect 3 tiers of actionability The centralised clinic has reviewed 21 patients nationally to test 23 highest actionability variants. The average referral to review time is 2 weeks. Conclusions: Precision oncology can play a role in familial cancer prevention. Deliberate collaboration and integration between precision research and relevant specialised care can lead to resource-optimised, equitable delivery of quality care.

Background: Real-time review of frozen sections underpins the quality of Mohs surgery. There is an unmet need for low-cost techniques that can improve Mohs surgery by reliably corroborating cancerous regions of interest and surgical margin proximity. Objective: To test that deep learning models can identify nonmelanoma skin cancer regions in Mohs frozen section specimens. Methods: Deep learning models were developed on archival images of focused microscopic views (FMVs) containing regions of annotated, invasive nonmelanoma skin cancer between 2015 and 2018, then validated on prospectively collected images in a temporal cohort (2019-2021). Results: The tile-based classification models were derived using 1423 focused microscopic view images from 154 patients and tested on 374 images from 66 patients. The best models detected basal cell carcinomas with a median average precision of 0.966 and median area under the receiver operating curve of 0.889 at 100x magnification (0.943 and 0.922 at 40x magnification). For invasive squamous cell carcinomas, high median average precision of 0.904 was achieved at 100x magnification. Limitations: Single institution study with limited cases of squamous cell carcinoma and rare nonmelanoma skin cancer. Conclusion: Deep learning appears highly accurate for detecting skin cancers in Mohs frozen sections, supporting its potential for enhancing surgical margin control and increasing operational efficiency.

Abstract Purpose Systematic repurposing of approved medicines for another indication may accelerate drug development in oncology. We present a strategy combining biomarker testing with drug repurposing to identify new treatments for patients with advanced cancer. Methods Tumours were sequenced with the Illumina TruSight Oncology 500 (TSO‐500) platform or the FoundationOne CDx panel. Mutations were screened by two medical oncologists and pathogenic mutations were categorised referencing literature. Variants of unknown significance were classified as potentially pathogenic using plausible mechanisms and computational prediction of pathogenicity. Gain of function (GOF) mutations were evaluated through repurposing databases Probe Miner (PM), Broad Institute Drug Repurposing Hub (Broad Institute DRH) and TOPOGRAPH. GOF mutations were repurposing events if identified in PM, not indexed in TOPOGRAPH and excluding mutations with a known Food and Drug Administration (FDA)‐approved biomarker. The computational repurposing approach was validated by evaluating its ability to identify FDA‐approved biomarkers. The total repurposable genome was identified by evaluating all possible gene‐FDA drug‐approved combinations in the PM dataset. Results The computational repurposing approach was accurate at identifying FDA therapies with known biomarkers (94%). Using next‐generation sequencing molecular reports (n = 94), a meaningful percentage of patients (14%) could have an off‐label therapeutic identified. The frequency of theoretical drug repurposing events in The Cancer Genome Atlas pan‐cancer dataset was 73% of the samples in the cohort. Conclusion A computational drug repurposing approach may assist in identifying novel repurposing events in cancer patients with no access to standard therapies. Further validation is needed to confirm a precision oncology approach using drug repurposing.

OPINION article Front. Oncol., 22 February 2023Sec. Cancer Epidemiology and Prevention Volume 13 - 2023 | https://doi.org/10.3389/fonc.2023.1074091

2594 Background: Despite immune checkpoint inhibitors (ICI) demonstrating efficacy in over 15 cancer types, evidence in most rare cancers remain scarce, reflecting the challenges of conducting prospective trials. This Australia-wide study reports real-world (RW) objective responses to ICIs targeting the programmed death-(ligand)1 (PD-1/PD-L1) pathway in a large precision oncology program, and associations between response and genomic alterations in rare cancers. Methods: This study was conducted within the framework of the MoST Program (ACTRN12616000908437), where adult patients (pts) with advanced solid tumors were screened using comprehensive genomic profiling (CGP). Only pts who received ICI after CGP were included in this analysis. The best overall response (BOR) to ICI was reported by the treating oncologist during the follow-up period. Best response was categorized as complete (CR), partial (PR), stable (SD), or progressive (PD). Two categories were defined: responders were individuals reported to have experienced CR or PR, while non-progressors were those with CR, PR, or SD. The association between tumor mutational burden (TMB) and response categories was assessed by area under the receiver operator characteristic curve (AUC). Odds ratios (OR) of specific genomic alterations associated with each category were also estimated. Results: Between Dec 2016 and Aug 2022, 4343 pts were screened; 3471 (80%) rare cancer pts, of whom 556 went on to 90 different ICI trials after undergoing CGP. In 273 pts treated with ICI where BOR was reported by the treating oncologist, the median survival was 17.3 months (95% CI 15.0 to 20.4). 13 pts (4.8%) had CR reported, including 8 pts with unapproved indications: 3 sarcomas, and 1 each, small cell carcinoma of unknown primary, adenoid cystic carcinoma, pituitary adenoma, thymoma, and pancreatic adenocarcinoma. 45 (16.5%) and 112 (41.0%) had PR and SD reported, respectively. High TMB, defined as ≥10 non-synonymous tumor mutations/megabase, was identified in 39 (14.3%) pts. TMB was associated with response (AUC 0.715, 0.630 to 0.800) and non-PD (AUC 0.600, 0.528 to 0.671) to ICI. Further exploratory analyses identified that alterations in EP300 (n = 7, OR, 9.8, 1.9 to 52), PTCH1 (n = 6, OR, 15.5, 1.7 to 141) , MSH6 and KMT2D (n = 6 each, OR, 7.7, 1.4 to 43) , and NF1 (n = 10, OR, 3.89, 1.1 to 13.9) were associated with CR/PR. Genomic ARID1A alterations (n = 18) were associated with non-PD (OR 5.16, 1.2 to 22.9), as were alterations in the SWI/SNF complex (n = 20, OR 3.64, 95% CI 1.0 to 12.8) . Conclusions: Notwithstanding their limitations, these real-world data suggest that rare cancer patients may also benefit from ICI. Further prospective investigations into pan-cancer genomic biomarkers of response are warranted. Clinical trial information: ACTRN12616000908437 .

Is it time to rethink the role of data and AI in cancer diagnosis and treatment through #informarkers?

5526 Background: Gynecological (gyne) cancers are highly diverse with distinct sites of origin and histological subtypes that can limit development of evidence-based therapies. Comprehensive genomic profiling (CGP) has an increasing role in characterizing clinically relevant molecular subsets and in identifying actionable biomarkers with potential to guide therapy selection. Methods: MoST (ACTRN12616000908437) is an Australia-wide precision oncology program for adult patients (pts) with advanced cancers and limited treatment options. Tumor specimens are analysed by CGP and genomic results tiered by the level of evidence supporting matched therapies (https://topograph.info). Pts are followed for subsequent treatment and survival. Here, we present data for the MoST gyne cancer cohort. Results: Between Sept 2016 and Oct 2022, 533 gyne tumors were sequenced, with included pts having a minimum 4 months (mo) follow-up. Key histotypes included: ovarian serous (n=162) and non-serous (n=46) epithelial tumors; uterine carcinomas (n=99) and sarcomas (n=108); cervical carcinomas (n=51); germ cell and sex-cord stromal tumors (n=18); carcinosarcomas (n=33); and vulva/vaginal tumors (n=16). The median number of reported variants was 3 (IQR 2-5) and tumor mutational burden 3.1 mut/Mb (IQR 1.3—5.5, Range 0—284); 9 (2%) tumors were microsatellite unstable; and 22 (4%) had high level loss-of-heterozygosity (confirmed on validated genome-wide assays). The most common pathways involved in this pan-gyne cohort were: p53 (n=287, 54%), PI3K/AKT (n=227, 43%), cell cycle (n=182, 34%), and mitogen-activated protein kinase (n=91, 17%). Pathogenic mutations in BRCA1/2 were identified in 29 tumors (5%; 18 in ovarian serous cancers), whereas 81 tumors (15%) had alterations in other homologous recombination genes, most commonly uterine sarcomas (n=32, 30%). Actionable genomic biomarkers matched to a clinically active treatment (TOPOGRAPH tier 1-3) were identified in 207 (39%) tumors. In 19 pts (3.5%) who received Tier 1-3 matched therapy after CGP, a trend towards longer survival was observed (median OS 22.3 mo, 95% CI 17.3 to not reached) compared to those receiving unmatched therapy (n=65, median OS 14.9 mo, 10.2 to 22.1, p=0.052) following CGP. No OS difference was seen in pts who received matched investigational therapy (Tier 3B/4, n=31, median OS 17.0 mo, 8.1 to NR) versus only unmatched therapy (n=118, median OS 14.0 mo, 11.3 to 22.5; HR 0.97, 0.57 to 1.64; p=0.91). Conclusions: CGP identified actionable genomic results in nearly half of advanced gyne cancers, with enrichment in particular histotypes that supports testing above current standard of care. Trends in prolonged OS with subsequent matched therapies may be better realized with earlier testing and improved drug/clinical trial access.

3101 Background: The Dutch Drug Rediscovery Protocol (DRUP, NCT02925234) and the Australian Cancer Molecular Screening and Therapeutic (MoST, ACTRN12616000931471) Program are similar non-randomized, multi-drug, pan-cancer trial platforms that aim to identify signals of clinical activity of molecularly matched targeted therapies or immunotherapies outside their approved indications. Here, we report results for advanced or metastatic pre-treated cancer patients with tumors harboring Cyclin D-CDK4/6 pathway alterations that were treated with CDK4/6 inhibitors palbociclib or ribociclib as monotherapy. Methods: Eligible adult patients had therapy-refractory solid malignancies with one of the following alterations: amplifications of CDK4, CDK6, CCND1, CCND2 or CCND3, or complete loss of CDKN2A or SMARCA4. Within MoST, all patients were treated with palbociclib, whereas in DRUP, palbociclib and ribociclib were assigned to different cohorts (defined by tumor type and alteration). The primary endpoints for this combined analysis were clinical benefit, defined as confirmed objective response or stable disease (SD) ≥16 weeks, and safety. Results: Among 139 enrolled patients 33 tumor types were represented, with glioblastoma multiforme (18%), sarcoma (13%), non-small cell lung cancer (9%) and pancreatic cancers (9%) being most common; 116 patients received palbociclib and 23 received ribociclib. In 112 evaluable patients, the objective response rate was 0% and clinical benefit rate at 16 weeks was 15% (17 cases of SD ≥16 weeks). Median progression-free survival was 4 months (95% CI 3-5 months) and median overall survival 5 months (95% CI 4-6 months). No unexpected toxicity was observed for either drug. Additional driver alterations were identified in 98% and 77% of patients based on whole genome sequencing (WGS) and sequencing next generation sequencing (NGS) analysis at baseline, respectively (Most common in WGS: TP53 (45%), KRAS (25%), PTEN (15%), SMAD4 (15%). Most common in NGS: TP53 (21%), EGFR (17%), TERT promoter (15%), KRAS (11%). Conclusions: Results show minimal clinical activity of palbociclib and ribociclib monotherapy in patients with pre-treated cancers harboring cyclin D-CDK4/6 pathway alterations. Our findings indicate that single agent use of palbociclib or ribociclib is not recommended. Furthermore, we demonstrate that merging data from similar precision oncology trials is feasible. This finding is especially relevant in the context of precision oncology, with rare molecular subsets and/or cancer histologies. Clinical trial information: NCT02925234 .

4093 Background: Despite advances in therapeutic strategies, advanced BTC continue to have poor outcomes. We examined the genomic composition of these cancers and differences in clinical outcomes based on therapies (tx) received. Methods: This study included all BTC patients (pts) undergoing comprehensive genomic profiling (CGP) through an Australia-wide precision oncology program, MoST (ACTRN12616000908437). The primary outcome was overall survival (OS) measured from start of first line (1L) systemic tx. The TOPOGRAPH knowledge base was used to determine genomic actionability of alterations identified, tiered by the strength of supportive clinical evidence. Tier 1/2 are regulatory body (TGA or FDA/EMA) approved therapies in BTC; tier 3A is supported by BTC-specific clinical evidence; 3B by clinical evidence inferred from another cancer type; tier 4, pre-clinical evidence. As targeted therapies are only approved in the subsequent-line setting, a further OS analysis was performed from start of second line tx (2L). Results: Between December 2016 and August 2022, 223 pts had CGP results available: 170 cholangiocarcinoma (99 intrahepatic, 46 extrahepatic, 25 unspecified primary site) and 53 gallbladder carcinomas. Of 211 (95%) pts who received any systemic tx, median OS (mOS) was 14.6 (95% CI: 12.2—15.4) months (mo) from the start of 1L tx. Pts having received immunotherapy had a mOS of 20.7 vs 13.9 mo (HR 0.67, 0.44—1.04; p=0.07). For 198 pts with actionable findings across TOPOGRAPH tiers, receipt of matched tx (n=37) was associated with a significantly longer mOS of 21.4 (15.0—31.8) compared with receipt of unmatched tx (n=161), mOS 12.6 mo (11.5C15.2, hazard ratio for death, HR 0.46, p<0.001). Pts with tier 1-3 actionable alterations who received matched tx had a median OS of 30.5 mo (95% CI: 18.8 - not reached, NR) compared with 12.1 mo (9.8—16.1, HR 0.39, p=0.02) if only unmatched tx received. Receipt of tier 3B/4 matched tx (n=13) only showed a trend towards longer survival, 15.6 mo vs unmatched 14.0 mo (HR 0.60, p=0.16). For 149 pts who received >1 line of systemic tx: 35 matched and 103 unmatched alone, mOS (measured from 2L tx) was 11.3 (5.7-28.4) compared with 8.3 mo (6.1-10.6) respectively (HR 0.67, p=0.10). A significantly longer OS was seen for matched vs unmatched, in pts receiving tier 1-3 tx: mOS 19.0 mo vs 8.3 mo (HR 0.43, p=0.04), but not for tier 3B/4, mOS 5.6 vs 6.7 mo HR 1.31, p=0.48. The most common genomic alterations were in TP53 (86, 39%), KRAS (59, 26%), CDKN2A (43, 19%), and ARID1A (29, 13%), while actionable findings commonly involved IDH1 (26, 12%), FGFR2 (20, 9%), ERBB2 (14, 6%), and BRAF (11, 5%). Conclusions: Receipt of genomically matched tx, particularly those supported by TOPOGRAPH tiers 1-3 evidence was associated with longer OS for pts with advanced BTC. Our results support the greater use of CGP in the management of these pts.

1540 Background: Biomarker actionability and therapy matching are two central concepts in precision oncology. However, the best strategy to align therapy with genomic alterations remains unclear. Here we report the updated results from a cohort study conducted in an Australian precision oncology program (MoST, ACTRN12616000908437), examining a therapy matching strategy based on comprehensive genomic profiling (CGP) results. Methods: All patients (pts) with rare or advanced solid tumours undergoing CGP from 2016 to 2021 after exhausting standard treatments were included. The primary outcome was overall survival (OS) from the date of CGP result, estimated using the Kaplan-Meier method. Pts were grouped according to tiers of actionability determined by matching against the TOPOGRAPH knowledge base ( https://topograph.info ) and stratified into clinically active (Tier 1-3, therapies with evidence from prospective trials), investigational (Tier 3B and 4, therapies with evidence from another cancer type, preclinical, or retrospective studies), or unmatched tier groups. To assess between-group differences in OS, hazard ratios (HR) were estimated in a time-varying Cox regression model adjusting for time to initiation of subsequent therapy. Results: This updated analysis included 3,383 pts (79% rare and less common). The median follow-up was 22.6 months (mo). For 2,065 pts who did not receive treatment after CGP, the median OS (mOS) was 8.2 mo (95% CI 7.4 to 9.0). For 1,318 pts who received ≥1 line of therapy after CGP, the mOS was 14.1 mo (13.4 to 15.2). 1,270 pts (38%) carried a genomic alteration linked to clinically active therapies (Tier 1-3). Of these, 116 (3.4%) received matched treatment after CGP, experiencing longer survival compared with 410 (32.2%) that received only unmatched therapy (mOS 21.2 v 12.8 mo, HR 0.58, 0.45 to 0.76, P<0.001). Whilst receiving a matched therapy in the investigational tier group (n=133, T3B/4) did not show significant differences in outcomes (mOS 14.5 v unmatched 12.8 mo, n=536, HR 0.88, 0.72 to 1.08, p=0.24), exploratory analyses identified differences in survival for a subset of 41 pts with Switch/Sucrose Non-Fermentable complex mutations receiving matched Tier 4 therapies (mOS 30.1 v 9.6 mo, HR 0.29, 0.17 to 0.51, P<0.0001). Pts receiving repurposed drugs that matched solely on biomarkers in non-cognate cancer types (Tier 3B) showed no survival difference over unmatched therapy (n=35 v 469, mOS 13.6 v 12.5 mo, HR 0.96, 0.65 to 1.41, p=0.83). Conclusions: This study provides insight into how biomarker-linked therapies can be rationally prioritised in rare and advanced cancer populations. Addressing the barriers of access to Tier 1-3 therapies may broaden the utility of genomic biomarker testing. Off-label drug repurposing without direct supporting evidence should only be undertaken in a clinical trial setting.

3127 Background: The antibody-drug conjugate T-DM1 is widely used for the treatment of HER2-positive metastatic breast cancer. Its activity in other advanced solid tumors harboring HER2 alterations identified by comprehensive genomic profiling (CGP) needs further characterization. Methods: The MoST program provides a precision oncology framework for screening patients (pts) by CGP to identify genomic alterations with potential to match to biomarker-directed clinical trials. This multi-center, single-arm phase 2 trial (ACTRN12619001265167) enrolled adult pts with refractory solid tumors (excluding breast and gastroesophageal cancers) with HER2 alterations. This trial recruited 2 groups of 16 pts (group 1: mutations, group 2: genomic amplification, defined as copy number ≥ 6 copies). The primary composite endpoint was objective tumor response (OTR) assessed by RECIST 1.1 and time-to-progression (TTP) ratio (defined as TTP on T-DM1: TTP1 on prior line of systemic therapy). Anti-tumor activity of T-DM1 was confirmed if ≥3 of each 16 pt group achieved an OTR. Key secondary endpoints were progression-free and overall survival (PFS and OS) and safety as assessed by CTCAE 5.0. Results: 32 pts had a median age of 64 years (interquartile range [IQR] 53 to 69); 94% an ECOG PS ≤1; 53% female; and median 2 (IQR 1 to 3.5) prior lines of systemic therapy. The cohort included non-small cell lung cancer (NSCLC, n=12), colorectal (CRC, n=5), salivary gland (SGC, n=5), ovarian (n=3), uterine (n=2), gallbladder (n=2), and 1 each of bladder, pancreas and cervix cancers. After a median follow-up of 17 months (mo), the primary endpoint was met with 7 pts (22%) achieving an OTR, including 3 pts (19%) in group 1 (2 NSCLC and 1 SGC) and 4 pts (25%) in group 2 (3 SGC, and 1 uterine serous carcinoma [USC]). Fourteen of 29 TTP-evaluable pts (48%) achieved a TTP ratio ≥1.3, including 10 pts without an OTR: equating to 53% (n=17) deriving clinical benefit. The median PFS and OS were 4.5 (95% CI 2.1 to 7.0) and 18.23 mo (95% CI 8.11 to not reached) respectively and 6 mo PFS rate 44% (95% CI 26 to 60%). The (NSCLC) responders in group 1 harbored exon 20 insertions (Y772_A775dup and G778_P780dup ) and the SGC, a L755S mutation. None of the S310Y/F mutations (n=5, including 2 NSCLCs) had an OTR. The USC was ERBB2 amplified (18 copies) on CGP, discordant with in situ hybridisation (ISH) testing results. Overall, 4 pts had CGP-amplified, ISH negative tumors, of whom 2 achieved an OTR. No responses were seen in CRC pts (all RAS/ BRAF-wildtype and IHC 2-3+). No new safety concerns for T-DM1 were reported. Conclusions: T-DM1 has anti-tumor activity across a heavily treated, diverse range of cancer types with HER2 alterations identified by CGP, including several unidentified by standard ISH testing. We await results from our partner trial in the first line advanced NSCLC setting to corroborate the group 1 findings. Clinical trial information: ACTRN12619001265167 .

https://data.mendeley.com/datasets/c3pytzc4fz/2 (Open access). Table S1 Table S2 Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

AbstractThe Dutch Drug Rediscovery Protocol (DRUP) and the Australian Cancer Molecular Screening and Therapeutic (MoST) Program are similar nonrandomized, multidrug, pan‐cancer trial platforms that aim to identify signals of clinical activity of molecularly matched targeted therapies or immunotherapies outside their approved indications. Here, we report results for advanced or metastatic cancer patients with tumors harboring cyclin D‐CDK4/6 pathway alterations treated with CDK4/6 inhibitors palbociclib or ribociclib. We included adult patients that had therapy‐refractory solid malignancies with the following alterations: amplifications ofCDK4,CDK6,CCND1,CCND2 or CCND3, or complete loss ofCDKN2A or SMARCA4. Within MoST, all patients were treated with palbociclib, whereas in DRUP, palbociclib and ribociclib were assigned to different cohorts (defined by tumor type and alteration). The primary endpoint for this combined analysis was clinical benefit, defined as confirmed objective response or stable disease ≥16 weeks. We treated 139 patients with a broad variety of tumor types; 116 with palbociclib and 23 with ribociclib. In 112 evaluable patients, the objective response rate was 0% and clinical benefit rate at 16 weeks was 15%. Median progression‐free survival was 4 months (95% CI: 3‐5 months), and median overall survival 5 months (95% CI: 4‐6 months). In conclusion, only limited clinical activity of palbociclib and ribociclib monotherapy in patients with pretreated cancers harboring cyclin D‐CDK4/6 pathway alterations was observed. Our findings indicate that monotherapy use of palbociclib or ribociclib is not recommended and that merging data of two similar precision oncology trials is feasible.

Intragenic CpG dinucleotides are tightly conserved in evolution yet are also vulnerable to methylation-dependent mutation, raising the question as to why these functionally critical sites have not been deselected by more stable coding sequences. We previously showed in cell lines that altered exonic CpG methylation can modify promoter start sites, and hence protein isoform expression, for the human TP53 tumor suppressor gene. Here we extend this work to the in vivo setting by testing whether synonymous germline modifications of exonic CpG sites affect murine development, fertility, longevity, or cancer incidence. We substituted the DNA-binding exons 5–8 of Trp53, the mouse ortholog of human TP53, with variant-CpG (either CpG-depleted or -enriched) sequences predicted to encode the normal p53 amino acid sequence; a control construct was also created in which all non-CpG sites were synonymously substituted. Homozygous Trp53-null mice were the only genotype to develop tumors. Mice with variant-CpG Trp53 sequences remained tumor-free, but were uniquely prone to dental anomalies causing jaw malocclusion (p < .0001). Since the latter phenotype also characterises murine Rett syndrome due to dysfunction of the trans-repressive MeCP2 methyl-CpG-binding protein, we hypothesise that CpG sites may exert non-coding phenotypic effects via pre-translational cis-interactions of 5-methylcytosine with methyl-binding proteins which regulate mRNA transcript initiation, expression or splicing, although direct effects on mRNA structure or translation are also possible.

e13564 Background: Measures of patient-reported outcome (PRO) are important metrics in cancer care. However, PROs are poorly captured in routine practice, and data collection may incur undue burden on patients. It remains unclear if electronic medical records (EMR) contain sufficient information to dynamically monitor PROs in patients undergoing intensive systemic therapy. Methods: Over a 6 week period, consecutive patients attending an outpatient chemotherapy unit completed two questionnaires (EORTC QLQ-C30 and NCI PRO-CTCAE) at each visit. The corresponding EMR, authored by oncologists and allied health providers, were extracted up to 4 weeks prior to the questionnaire date. Random forest algorithm was used to predict each dichotomized PRO class using bag-of- n-grams extracted from the text. The classification performance was assessed by 8-fold cross-validation, using the area under receiver operating characteristic curve (AUC) as the metric. This study is part of the ePERSIST (electronic phenotyping, event retrieval, and case summarisation in solid tumours) project, exploring methods for extracting structured variables from EMR to support oncology research. Results: 115 patients (157 visits to the chemotherapy unit) completed up to 6 sets of questionnaires each. Overall, the median quality-of-life (QOL) score of QLQ-C30, QL2, was 67 (IQR 50 to 83). Machine learning predicted low QL2 score with mean AUC of 0.710 (95% CI 0.630 to 0.791). At the Bonferroni threshold of 0.00025, machine learning significantly predicted several components of QLQ-C30: PF2 (mean AUC 0.722, 0.633 to 0.812), AP (0.725, 0.630 to 0.819), CO (0.686, 0.607 to 0.764), FI (0.677, 0.598 to 0.755), PA (0.696, 0.603 to 0.787), FA (0.686, 0.584 to 0.787), and RF2 (0.717, 0.595 to 0.839). Conversely, EMR could only be used to significantly predict 4 of 13 PRO-CTCAE categories: cutaneous (0.745, 0.659 to 0.832), oral (0.734, 0.630 to 0.838), cardiovascular (0.675, 0.593 to 0.758), and gastrointestinal (GI, 0.742, 0.625 to 0.860), or 15 of 79 (19%) of PRO-CTCAE items related to adverse events including cutaneous (radiation burns, hypohidrosis, rash), oral (anorexia, dysphagia, dysgeusia), and GI symptoms (constipation, bloating), and others (anxiety, hoarseness, pain, erectile dysfunction). An exploratory analysis revealed that specific keywords linked to the PRO items were present in only one (11%) QLQ-C30 and 4 (5%) PRO-CTCAE items. Conclusions: The use of machine learning on clinical text predicts QOL and certain patient-reported adverse events with moderate accuracy in individuals undergoing intensive systemic treatment, suggesting its potential utility in syndromic monitoring where PRO is not formally assessed. Given many items cannot be accurately extracted, however, obtaining information directly from patients through questionnaires may still be required because of limited documentation by clinicians.

ABSTRACTImmune checkpoint blockade impedes the negative regulatory signals for T-cell response and permits more effective immune detection and eradication of cancer cells. This single-arm phase II clinical trial (ACTRN12616001019493) within the Molecular Screening and Therapeutics (MoST) program evaluates the clinical activity and safety of combination immunotherapy with durvalumab and tremelimumab in patients with advanced cancers, prioritsing rare cancers (<6 per 100,000 annual incidence) and patients having failed standard treatments for their cancer type.MethodsEligible patients were determined by the molecular tumour board based on the absence of actionable genomic findings (n=64) and biomarker enriched (n=48) at screening. Patients received durvalumab 1500 mg and tremelimumab 75 mg every four weeks for 4 cycles, followed by durvalumab alone for another 9 cycles. The primary endpoint was progression-free survival at 6 months (PFS6) and secondary endpoints included objective response, time to progression (TTP) on trial to TTP on prior therapy (TTP2/TTP1>1.3), overall survival and treatment tolerability.ResultsBetween December 2016 and 2019, 112 patients were enrolled on the study. There was a female predominance (55%), most had an ECOG performance status of 0 (66%), aged <65 years (75%), with rare cancers (84%). The PFS6 rate was 32% (95% CI 23 to 40%); 16 of 112(14%) achieved an objective response; TTP2/TTP1>1.3 for 22 of 63 (35%) patients with an evaluable ratio; median overall survival 11.9 months (95% CI 11.0 to 14.8), and there were no new safety concerns. High tumour cell PD-L1 correlated with improved PFS and OS and TMB with PFS alone. More PD-1+CD4+ T-cells and circulating follicular T-helper (cTfh) cells at baseline were strongly associated with better PFS and OS.ConclusionDurvalumab plus tremelimumab demonstrated a signal of clinical activity in treatment-refractory patients with rare cancers. A PFS6 of 32% and 35% of patients achieving a TTP2/TTP1>1.3 suggests an improved disease trajectory on trial. Translational correlates provided insights into biological associations with clinical outcomes across tumour types.

3073 Background: Comprehensive genomic profiling (CGP) is increasingly used to guide therapy selection in advanced cancer patients who have exhausted standard therapy options. Here we assess the utility of Therapy Oriented Precision Oncology Guidelines for Recommending Anticancer Pharmaceuticals (TOPOGRAPH) to guide matching of drug treatments based on CGP in this setting. Methods: This study was conducted in an Australia-wide precision oncology program, the Molecular Screening and Therapeutics Study (MoST, ANZCTR registration ACTRN12616000908437). All patients with advanced cancer after exhausting standard treatments underwent CGP in 2016-2021 were stratified into cohort A (no further therapy received) and B (received ≥1 therapy after CGP). The primary outcome was overall survival (OS) estimated by the Kaplan-Meier method, using the log rank test to assess between-group differences. TOPOGRAPH matched the treatment history to the CGP results, stratified into clinically active (Tiers 1-3, T1-3), investigational (T3B/4), inactive (R2) or unmatched groups. Results: Over a median follow-up of 21.7 months (mo) for 2852 patients (75% with rare cancers, n = 2150), the median OS (mOS) from the date of CGP result was 7.0 mo (95% CI 6.4-7.6) for cohort A (n = 1562) and 15.8 mo (95% CI 14.5-16.9) for cohort B (n = 1290). In both cohorts, patients with CGP results matching any TOPOGRAPH tier (T1-4) had shorter OS compared to patients without a matching tier (A: 6.4 v 20.5 mo, hazard ratio for death [HR] 2.15, p<0.001; B: 14.7 v 23.6 mo, HR 1.43, p<0.001). Patients in cohort B receiving matched therapy (n=342, 27%) had a longer mOS than 948 patients who received only unmatched therapy (16.9 v 10.4 mo, HR 0.70, p<0.001). For CGP results matched to T1-3, 122 patients who received a T1-3 therapy had a significantly longer mOS than those who received unmatched therapy (22.1 v 9.8 mo, HR 0.51, p<0.001). For CGP results matched only to T3B/4, a trend toward longer mOS was observed in patients receiving matched therapy in T3B/4 (n = 138, 14.5 v unmatched 10.0 mo, HR 0.81, P = 0.07). In tier-matched analysis, the mOS were not significantly different between patients who received genomics matched v unmatched therapy in T3B (matching outside cognate histotypes, n = 48 v 508, 11.9 v 9.7 mo, HR 0.84, p = 0.36) and T4 (n = 32 v 134; therapy with preclinical/early clinical evidence, 17.1 v 12.2 mo, HR 0.69, p = 0.17). Conclusions: TOPOGRAPH is prognostic and likely predictive of treatment effect based on CGP, supporting its utility in guiding molecular therapy selection in patients who have exhausted standard treatment options. [Table: see text]