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Sat Aug 1, 2020, 08:32 PM

The National Lung Matrix Trial of personalized therapy in lung cancer

The paper I'll discuss in this post is this one: The National Lung Matrix Trial of personalized therapy in lung cancer (Gary Middleton, Peter Fletcher, Sanjay Popat, Joshua Savage, Yvonne Summers, Alastair Greystoke, David Gilligan, Judith Cave, Noelle O’Rourke, Alison Brewster, Elizabeth Toy, James Spicer, Pooja Jain, Adam Dangoor, Melanie Mackean, Martin Forster, Amanda Farley, Dee Wherton, Manita Mehmi, Rowena Sharpe, Tara C. Mills, Maria Antonietta Cerone, Timothy A. Yap, Thomas B. K. Watkins, Emilia Lim, Charles Swanton & Lucinda Billingham, Nature 583, 807–812 (2020))

The authors are all from the UK, where everyone has died from having a single payer health care system, as well we know from the Pravda/Völkischer Beobachter of America, fair and balanced FOX News, the official mouthpiece of Dr. Trump and the chloroquine demon seed doctors, and official Jim Jones Memorial Koolaid Kure-all Klub (KKK).

Cancer, as most people know, is not actually one disease, and it turns out that even cancers in and of particular organs are not single diseases. For example, in breast cancer, there is ER+, PR+, HER2+ and triple negative. These are not equivalent diseases. My sister-in-law had ER+ cancer - I wept for joy when I found this out, of course, after finding out that she had cancer since ER+ is treatable - and her cancer proved quite treatable; she kept her breast and is 5 years into remission after surgical excision, chemotherapy and radiation therapy. Other types of breast cancer are far more problematic.

It gets deeper than that on a molecular biology level, and the use of automatic genetic testing has allowed for the development of targeted or "personalized" treatment. That is the subject of this paper.

My father, a smoker who used to joke about "cancer sticks" that he "needed" died from lung cancer. Perhaps in a personalized medicine word he might have survived longer; he was dead within a few months of diagnosis.

From the paper's introduction:

In the case of cancer treatment, stratified medicine is a therapeutic strategy whereby the genotype of a tumour is used to match the patient to an appropriate targeted therapy. This strategy was first realized for the treatment of NSCLC when mutations in the tyrosine kinase domain of the epidermal growth factor receptor (EGFR) were identified as the molecular basis of the clinical responses observed in patients treated with the EGFR tyrosine kinase inhibitor gefitinib1. In NSCLC, the majority of targetable alterations tend to occur in the cancers of patients who have never smoked or who are former light smokers. In tobacco-associated lung adenocarcinoma (LUAD) there are few actionable aberrations, and in squamous-cell lung cancer (LUSC) there are no options for targeted therapy.

Here we report the current results of the ongoing National Lung Matrix Trial (NLMT), the largest national NSCLC umbrella study. NSCLC genotyping using next-generation sequencing (NGS) is used to stratify patients into one of 22 single-arm signal-of-activity studies, testing 8 different drugs (Fig. 1). Screening was performed on the 28-gene NGS panel from Cancer Research UK’s Stratified Medicine Programme (SMP2) (details provided in Methods). To embed the programme into National Health Service (NHS) practice, the majority of tumours sequenced were obtained from formalin-fixed paraffin-embedded material surplus to requirements of the diagnostic work-up. Aberrations in targeted genes were tiered for oncogenic relevance using published data: tier 1 or tier 2 aberrations were eligible for inclusion4.


There's that NHS practice note. Terrible, terrible, terrible, right Rush Limbaugh, you bag of physical tumors not quite as bad as the tumor you've been on our culture, you racist lump of cancer eaten lard. May you rot in hell with the other racists.

Sorry. Can't help myself.

Some graphics:



The caption:

Patients are stratified using the 28-gene NGS panel test results from SMP2, and the trial is currently testing 8 different targeted drugs (A–H) in 22 different actionable biomarker cohorts. The trial also includes a cohort of patients with no actionable aberrations (NA).




The caption:

he flow diagram shows the progress of patients through SMP2 and NLMT arms A–H as of 30 November 2019




The caption:

orest plots show Bayesian estimates and 95% credible intervals for true values of median PFS, DCB rate and OR rate. Purple is used to highlight estimates for which PFS is the primary outcome measure, with vertical lines showing a pre-specified clinically relevant target of a median PFS of 3 months. Green or blue is used to highlight estimates for which DCB and OR rates are co-primary outcome measures, with vertical lines showing pre-specified clinically relevant target rates of 40% or 30%, respectively. Cohorts that are closed to recruitment are represented by solid lines and those still open are represented by dashed lines. Bayesian estimates are the medians of the posterior probability distributions derived from the current data and minimally informative priors. Because the trial is ongoing and the follow-up is not complete (including in some closed cohorts), these estimates are subject to change as the trial continues.




The caption:



The caption:

a, Top, waterfall plot shows, for each patient, the best percentage change in sum of target lesion diameters according to RECIST v.1.1. Bars are coloured according to the patient’s smoking history. Patients who discontinued before assessment, or had a value greater than 100% were capped at 100%. Bottom, forest plots show Bayesian estimates (with 95% credible intervals) of OR rates, grouped according to the smoking history of the patients. b, As for a, but coloured and grouped according to the histology of the tumour.


The results of the study are ambiguous, reflecting the genetic complexity of cancers, particularly in this case, among smokers, but the work presents some pathways forward:

Pre-clinical work is essential to identify promising biomarker–drug combinations, but the models used must recapitulate the genomic context and evolutionary trajectory of the targeted genomic alteration. Tobacco-associated NSCLCs harbour many more clonal mutations compared with NSCLCs in non-smokers11, which increases the chance that other oncogenic drivers could co-exist with the targeted genomic aberration. Ongoing genomic instability driven largely by tobacco exposure, APOBEC and mitotic clock signatures12—combined with extensive somatic copy-number alterations (SCNAs)—may also lead to the rapid evolution of resistance. A reduction in clinical benefit with increasing cumulative smoking duration13 and higher complexity of the mutational landscape14 has been demonstrated in patients with EGFR mutations treated with EGFR tyrosine kinase inhibitors. Although we relied on extensive pre-clinical data to inform our biomarker–drug selections, a substantial amount of data was generated using models that lacked other genomic aberrations besides the targeted alteration. Genetically engineered mouse models of NSCLC have mutational burdens more than 100-fold lower than that of human disease15. Carcinogen-induced models have few SCNAs16. Non-malignant cells that are engineered to harbour single genomic aberrations (as used to select treated with AZD454717) fail to replicate genomic complexity. The results of targeting common SCNAs were disappointing. There was a stark difference in the activity of crizotinib in patients with cancers that harbour MET amplification compared with MET exon 14 mutations: the former is characterized by greater genomic instability and can be heterogeneous, the latter often occurs in non-smokers in cancers without concurrent driver mutations18. Chromosomal copy-number amplicons can encode multiple genes, all of which might subtly affect the phenotype. Using two genomic datasets—TCGA and TRACERx (tracking non-small cell lung cancer evolution through therapy)—we investigated whether this was the case with PIK3CA amplification. We found that there are indeed a substantial number of potential drivers that are co-amplified with PIK3CA and, furthermore, that there is considerable heterogeneity of amplicon size across individual tumours (Extended Data Figs. 5, 6).


Lung cancer, is usually a bad thing, but not always. Rush Limbaugh has it.

I happen to know it can be a very ugly way to die, and coldly and cruelly, without any sense of forgiveness, in his case all ugliness is merited.

Enjoy the rest of the weekend safely.





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