Transcriptional phenocopies of deleterious<i>KEAP1</i>mutations dictate survival outcomes in lung cancer treated with immunotherapy
Abstract Mutational models denoting KEAP1-NRF2 pathway activation have emerged as determinants of survival outcomes in non-small cell lung cancer (NSCLC). Hypothesizing that genetically distinct tumors recapitulate the transcriptional footprint ofKEAP1mutations (KEAPness), we identified a KEAP1-NRF2-related gene set shared by tumors with and without pathway mutations. KEAPness-dominant tumors were associated with poor survival outcomes and immune exclusion in two independent cohorts of immunotherapy-treated NSCLC (SU2C and OAK/POPLAR). Moreover, patients with KEAPness tumors had survival outcomes comparable to theirKEAP1-mutant counterparts. In the TRACERx421, KEAPness exhibited limited transcriptional intratumoral heterogeneity and an immune-excluded microenvironment, as highlighted by orthogonal methods for T cell estimation. This phenotypic state widely occurred across genetically divergent tumors, exhibiting shared and private cancer genes under positive selection when compared toKEAP1-mutant tumors. Collectively, we discovered the pervasive nature of the KEAPness phenotypic driver across evolutionary divergent tumors. This model outperforms mutation-based classifiers in predicting survival outcomes..
Medienart: |
Preprint |
---|
Erscheinungsjahr: |
2023 |
---|---|
Erschienen: |
2023 |
Enthalten in: |
bioRxiv.org - (2023) vom: 18. Dez. Zur Gesamtaufnahme - year:2023 |
---|
Sprache: |
Englisch |
---|
Beteiligte Personen: |
Scalera, Stefano [VerfasserIn] |
---|
Links: |
Volltext [kostenfrei] |
---|
Themen: |
---|
doi: |
10.1101/2023.10.30.23297743 |
---|
funding: |
|
---|---|
Förderinstitution / Projekttitel: |
|
PPN (Katalog-ID): |
XBI041364724 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | XBI041364724 | ||
003 | DE-627 | ||
005 | 20231219091123.0 | ||
007 | cr uuu---uuuuu | ||
008 | 231031s2023 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1101/2023.10.30.23297743 |2 doi | |
035 | |a (DE-627)XBI041364724 | ||
035 | |a (biorXiv)10.1101/2023.10.30.23297743 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Scalera, Stefano |e verfasserin |4 aut | |
245 | 1 | 0 | |a Transcriptional phenocopies of deleterious<i>KEAP1</i>mutations dictate survival outcomes in lung cancer treated with immunotherapy |
264 | 1 | |c 2023 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
520 | |a Abstract Mutational models denoting KEAP1-NRF2 pathway activation have emerged as determinants of survival outcomes in non-small cell lung cancer (NSCLC). Hypothesizing that genetically distinct tumors recapitulate the transcriptional footprint ofKEAP1mutations (KEAPness), we identified a KEAP1-NRF2-related gene set shared by tumors with and without pathway mutations. KEAPness-dominant tumors were associated with poor survival outcomes and immune exclusion in two independent cohorts of immunotherapy-treated NSCLC (SU2C and OAK/POPLAR). Moreover, patients with KEAPness tumors had survival outcomes comparable to theirKEAP1-mutant counterparts. In the TRACERx421, KEAPness exhibited limited transcriptional intratumoral heterogeneity and an immune-excluded microenvironment, as highlighted by orthogonal methods for T cell estimation. This phenotypic state widely occurred across genetically divergent tumors, exhibiting shared and private cancer genes under positive selection when compared toKEAP1-mutant tumors. Collectively, we discovered the pervasive nature of the KEAPness phenotypic driver across evolutionary divergent tumors. This model outperforms mutation-based classifiers in predicting survival outcomes. | ||
650 | 4 | |a Biology |7 (dpeaa)DE-84 | |
650 | 4 | |a 570 |7 (dpeaa)DE-84 | |
700 | 1 | |a Ricciuti, Biagio |4 aut | |
700 | 1 | |a Marinelli, Daniele |4 aut | |
700 | 1 | |a Mazzotta, Marco |4 aut | |
700 | 1 | |a Cipriani, Laura |4 aut | |
700 | 1 | |a Bon, Giulia |4 aut | |
700 | 1 | |a Schiavoni, Giulia |4 aut | |
700 | 1 | |a Terrenato, Irene |4 aut | |
700 | 1 | |a Federico, Alessandro Di |4 aut | |
700 | 1 | |a Alessi, Joao V. |4 aut | |
700 | 1 | |a Fanciulli, Maurizio |4 aut | |
700 | 1 | |a Ciuffreda, Ludovica |4 aut | |
700 | 1 | |a Nicola, Francesca De |4 aut | |
700 | 1 | |a Goeman, Frauke |4 aut | |
700 | 1 | |a Caravagna, Giulio |4 aut | |
700 | 1 | |a Santini, Daniele |4 aut | |
700 | 1 | |a Maria, Ruggero De |4 aut | |
700 | 1 | |a Cappuzzo, Federico |4 aut | |
700 | 1 | |a Ciliberto, Gennaro |4 aut | |
700 | 1 | |a Jamal-Hanjani, Mariam |4 aut | |
700 | 1 | |a Awad, Mark M. |4 aut | |
700 | 1 | |a McGranahan, Nicholas |4 aut | |
700 | 1 | |a Maugeri-Saccà, Marcello |4 aut | |
773 | 0 | 8 | |i Enthalten in |t bioRxiv.org |g (2023) vom: 18. Dez. |
773 | 1 | 8 | |g year:2023 |g day:18 |g month:12 |
856 | 4 | 0 | |u http://dx.doi.org/10.1101/2023.10.30.23297743 |z kostenfrei |3 Volltext |
912 | |a GBV_XBI | ||
951 | |a AR | ||
952 | |j 2023 |b 18 |c 12 |