Tier R2: Therapies predicted to not have activity<\/li>\n<\/ul>\nThe analysis included data from 3,383 adults (mean age, 57.1 years; standard deviation, 14.3; 53% women) with advanced or metastatic cancers who had exhausted all standard systemic therapeutic options and who underwent genomic profiling between June 2016 and December 2021.<\/p>\n
The most common malignancies included sarcoma (19.3%), colorectal cancer (10.2%) and pancreatic cancer (8.5%). Lin, Thomas and colleagues classified 71.7% of participants with a \u201crare\u201d cancer.<\/p>\n
OS from the date of genomic profiling served as the primary endpoint.<\/p>\n
\u201cPrecision oncology has long operated on an appealingly simple promise: identify the right mutation and find the right drug,\u201d Lin said. \u201cHowever, physicians working at the coalface, in the clinic and at molecular tumor board meetings, know the reality is considerably more complex. When a patient hands you a dense genomic report after exhausting standard options, the question is rarely whether a mutation is present. The harder question is, how strong is the clinical evidence that this specific drug will meaningfully alter the course of this specific cancer?\u201d<\/p>\n
\u2018That\u2019s problematic\u2019<\/h2>\n Overall, 88.8% of patients had a tier 1 to 4 biomarker, including 37.5% with a tier 1 to 3A target. However, only 39% of the study population received additional therapy based on genomic profiling.<\/p>\n
\u201cThat\u2019s problematic,\u201d Thomas said. \u201cIt doesn\u2019t relate to the science. It relates to the availability of drugs, either through reimbursed access or through clinical trials. Frankly, we\u2019ve got a bit of work to do to increase the number of treatment options that these patients can access.\u201d<\/p>\n
After median follow-up of 22.6 months, 63% of the cohort died.<\/p>\n
The study population had a median OS of 11.3 months, but patients who received additional genomic-based care had substantially longer survival (median OS, 14.1 months vs. 8.2 months).<\/p>\n
Among patients who did not receive additional therapy, those who had a tier 1 to 4 target had significantly shorter survival than those without a matching target (median OS, 7.1 months vs. 30.1 months; adjusted HR = 1.75; 95% CI, 1.38-2.21).<\/p>\n
Among patients who received additional therapy, 29% received treatment matched to tier 1 to 4 biomarkers. Those who had a tier 1 to 3A biomarker and got matched treatment had significantly longer OS than those who received unmatched therapy (21.2 months vs. 12.8 months; aHR = 0.6; 95% CI, 0.44-0.82). Patients who had a tier 3B to 4 biomarker and received matched therapy had similar survival as those who received unmatched care (14.5 months vs. 12.8 months). Among those who had a tier 3B biomarker specifically, treatment with matched therapy did not result in significantly longer OS, either.<\/p>\n
\u201cBiological context matters immensely in drug selection,\u201d Lin said. \u201cA classic example is the BRAF<\/i> V600 mutation. When found in melanoma, it is highly responsive to targeted treatment, but that same mutation in colorectal cancer behaves entirely differently and requires a completely different treatment paradigm. As oncologists working in the clinic, we should reconsider the appropriateness of reflexive molecular drug repurposing and instead direct patients toward appropriately designed clinical trials.\u201d<\/p>\n
Researchers acknowledged study limitations, including use of TOPOGRAPH for tiering medications.<\/p>\n
\u201cWhile our study provides compelling observational evidence that the TOPOGRAPH tiering system stratifies clinical outcomes in a meaningful way, definitive prospective and comparative evaluation is needed to compare it with other frameworks, such as European Society for Medical Oncology Scale for Clinical Actionability of Molecular Targets,\u201d Lin said. \u201cAs an oncology community, we need to work together to understand the best strategy for moving forward to underpin clinical decision-making at scale.\u201d<\/p>\n
\u2018We need to increase access\u2019<\/h2>\n Both Lin and Thomas highlighted the importance of improving access to matched treatments in the future.<\/p>\n
\u201cOverall, 39% of patients [in our study] had a treatment recommendation which we show would extend survival, but only 3.4% of that group, 1 in 10, actually went on to receive treatment,\u201d Thomas said. \u201cAt the very least, one would expect that every patient who is dying of cancer who carries a biomarker that would extend survival would have an option to access those treatments.\u201d<\/p>\n
Thomas noted only 8% of patients with cancer in Australia currently participate in clinical trials.<\/p>\n
\u201cWe need to increase access to clinical trials, and for the drugs that are at the right stage, those drugs need to pass through our regulatory process so they do become a standard of care,\u201d he said.<\/p>\n
Identifying barriers to treatments could increase uptake of matched therapies.<\/p>\n
\u201cWhether [low uptake] is due to clinical ineligibility, drug access, regulatory hurdles, reimbursement issues or patient preference needs to be further studied,\u201d Lin said. \u201cGiven the limitations of our data, which extend back to 2021, we also need to continue to examine if those dynamics have evolved over the study period as access has improved.\u201d<\/p>\n
Because the field is \u201cconstantly moving,\u201d systems need to be refined so clinicians have the most updated information on who should receive matched genomic therapies, Thomas said.<\/p>\n
\u201cSince that trial was conducted, the same programs have continued, and currently our recommendation rate is not 65%, it\u2019s 85%, and the actionability rate that will extend survival has jumped from 39% to 45%,\u201d Thomas explained. \u201cI\u2019m expecting that trend to continue. In fact. I\u2019m expecting that by 2035, every patient that we screen should have a biomarker that would predict at least that there is a matched drug, if not an excellent match drug, and at least half of those patients will have a drug available that will double their survival.\u201d<\/p>\n
\u201cThe future of genomic medicine in oncology does not rest primarily on sequencing technology becoming cheaper or faster,\u201d Lin added. \u201cRather, it rests on building the clinical trial ecosystems, the international data-sharing infrastructure, and the decision-support frameworks that allow us to convert genomic information into durable, evidence-based patient benefit. That will be as much a global scientific and institutional challenge as a technological one.\u201d<\/p>\n
For more information:<\/h2>\n Frank P. Lin, MB ChB, PhD,<\/b> can be reached at frank.lin@sydney.edu.au.<\/p>\n
David M. Thomas, MBBS, PhD,<\/b> can be reached at dmthomas@unsw.edu.au.<\/p>\n\n
\n
Published by:<\/span>\n
Sources\/Disclosures<\/h3>\n Source: <\/h2>\n
JAMA Oncol<\/i>. 2026;doi:10.1001\/jamaoncol.2026.0127.<\/p>\n\n
Disclosures: <\/strong>
<\/p>\n
\n
\n
<\/p>\n
Ask a clinical question<\/strong> and tap into Healio AI’s knowledge<\/strong> base.<\/p>\n
<\/p>\nPubMed, enrolling\/recruiting trials, guidelines<\/li>\n
<\/p>\n
Clinical Guidance, Healio CME, FDA news<\/li>\n
<\/p>\n
Healio’s exclusive daily news coverage of clinical data<\/li>\n
\n <\/ul>\n
Learn more<\/button>\n <\/div>\n<\/div>\n
![\"hemonc](\"https:\/\/www.healio.com\/~\/media\/h5\/feature\/news\/publogos\/hot.svg?la=en&h=24&w=141&hash=2F86D471C8514C0E334E329AA799E8B4\")
\n <\/div>\n<\/p><\/div>\n<\/p><\/div>\n