For melanoma/lung cohorts, 58 patient samples and data were procured based on availability of tissue and were not collected according to a prespecified power analysis. These samples included 48 melanoma samples and 10 lung cancer samples. Included in these 58 samples were 8 relapse specimens (50 baseline pre–anti–PD-1 therapy), of which 5 were matched to a pre–anti–PD-1 therapy sample. Of these, 3 pairs were successfully RNA sequenced, 5 pairs were successfully scored for LAG-3 IHC, and 4 had sufficient tissue for FCRL6 IHC.
Total RNA quality was assessed using the 2200 Tapestation (Agilent). At least 20 ng DNase-treated total RNA, with at least 30% of the RNA fragments with a size >200 nt, was used to generate RNA Access libraries (Illumina) following the manufacturer’s recommendations. Library quality was assessed using the 2100 Bioanalyzer (Agilent), and libraries were quantitated using KAPA Library Quantification Kits (KAPA Biosystems). Pooled libraries were subjected to 75-bp paired-end sequencing according to the manufacturer’s protocol (Illumina HiSeq3000). Bcl2fastq2 Conversion Software (Illumina) was used to generate demultiplexed Fastq files.
QC for the paired-end raw sequencing reads of all samples was performed using FastQC for the analysis of sequence quality, GC content, the presence of adaptors, overrepresented k-mers, and duplicated reads. Sequencing reads were mapped to human reference genome GRCH38 (release-85, Ensembl) using STAR 2.2.1 with 2-pass mapping (53, 54). QC for read alignment and mapping was evaluated with RSeQC for sequencing saturation, mapped read clipping profile, mapped read distribution, and coverage uniformity. The transcripts per million (TPM) values were calculated using RSEM (56) and used to assess the global quality and reproducibility of the RNA-sequencing data set and exported for downstream data analyses.
Sample | Patient_ID | Sample_ID | TUMOR_TYPE | GROUP | IMMUNE_THERAPY | IMMUNE_RESPONSE | HLA_DR |
---|---|---|---|---|---|---|---|
P3437_JMB_001 | 7 | 7_pre | MEL | BASELINE | anti-PD1 | CR | 0.58 |
P3437_JMB_011 | 8 | 8_pre | LUNG | BASELINE | anti-PD1 | PR | 0.00 |
P3437_JMB_012 | 9 | 9_pre | LUNG | BASELINE | anti-PD1 | PD | NA |
P3437_JMB_014 | 10 | 10_pre | LUNG | BASELINE | anti-PD1 | PD | 0.02 |
P3437_JMB_015 | 1 | 1_pre | MEL | BASELINE | anti-PD1 | PR | NA |
P3437_JMB_016 | 1 | 1_post | MEL | PROGRESSION | anti-PD1 | RELAPSE | NA |
P3437_JMB_017 | 4 | 4_postB | MEL | PROGRESSION | anti-PD1 | RELAPSE | 0.43 |
P3437_JMB_018 | 4 | 4_postC | MEL | PROGRESSION | anti-PD1 | RELAPSE | NA |
P3437_JMB_019 | 3 | 3_pre | MEL | BASELINE | anti-PD1 | MR | NA |
P3437_JMB_002 | 11 | 11_pre | MEL | BASELINE | anti-PD1 | PD | 0.00 |
P3437_JMB_020 | 3 | 3_post | MEL | PROGRESSION | anti-PD1 | RELAPSE | NA |
P3437_JMB_021 | 12 | 12_pre | MEL | BASELINE | anti-PD1 | PR | 0.00 |
P3437_JMB_022 | 13 | 13_pre | MEL | BASELINE | anti-PD1 | PD | 0.70 |
P3437_JMB_023 | 14 | 14_pre | MEL | BASELINE | anti-PD1 | PR | 0.00 |
P3437_JMB_026 | 15 | 15_pre | LUNG | BASELINE | anti-PD1 | PD | 0.00 |
P3437_JMB_027 | 2 | 2_pre | MEL | BASELINE | anti-PD1 | PR | NA |
P3437_JMB_028 | 2 | 2_post | MEL | PROGRESSION | anti-PD1 | RELAPSE | NA |
P3437_JMB_003 | 16 | 16_pre | MEL | BASELINE | anti-PD1 | CR | 0.83 |
P3437_JMB_004 | 17 | 17_pre | MEL | BASELINE | anti-PD1 | PD | 0.01 |
P3437_JMB_040 | 18 | 18_pre | LUNG | BASELINE | anti-PD1 | NA | 0.00 |
P3437_JMB_041 | 19 | 19_pre | MEL | BASELINE | anti-PD1 | CR | 0.00 |
P3437_JMB_043 | 20 | 20_pre | LUNG | BASELINE | anti-PD1 | SD | 0.60 |
P3437_JMB_044 | 21 | 21_pre | MEL | BASELINE | anti-PD1 | PR | 0.05 |
P3437_JMB_045 | 22 | 22_pre | LUNG | BASELINE | anti-PD1 | PD | 0.00 |
P3437_JMB_046 | 23 | 23_pre | MEL | BASELINE | anti-PD1 | MR | 0.00 |
P3437_JMB_047 | 24 | 24_pre | MEL | BASELINE | anti-PD1 | PD | 0.25 |
P3437_JMB_048 | 25 | 25_pre | MEL | BASELINE | anti-PD1 | PD | 0.00 |
P3437_JMB_049 | 26 | 26_pre | MEL | BASELINE | anti-PD1 | MR | 0.01 |
P3437_JMB_005 | 27 | 27_pre | MEL | BASELINE | anti-PD1 | CR | 0.63 |
P3437_JMB_050 | 28 | 28_pre | MEL | BASELINE | anti-PD1 | CR | 0.05 |
P3437_JMB_051 | 29 | 29_pre | MEL | BASELINE | anti-PD1 | PD | NA |
P3437_JMB_053 | 30 | 30_pre | MEL | BASELINE | anti-PD1 | CR | 0.00 |
P3437_JMB_055 | 31 | 31_pre | MEL | BASELINE | anti-PD1 | PR | 0.00 |
P3437_JMB_058 | 32 | 32_pre | MEL | BASELINE | anti-PD1 | PD | 0.00 |
P3437_JMB_006 | 33 | 33_pre | MEL | BASELINE | anti-PD1 | PR | 0.78 |
P3437_JMB_060 | 34 | 34_pre | MEL | BASELINE | anti-PD1 | PR | 0.02 |
P3437_JMB_067 | 4 | 4_postA | MEL | PROGRESSION | anti-PD1 | RELAPSE | 0.43 |
P3437_JMB_069 | 35 | 35_pre | MEL | BASELINE | anti-PD1 | PD | 0.00 |
P3437_JMB_007 | 36 | 36_pre | MEL | BASELINE | anti-PD1 | PR | 0.10 |
P3437_JMB_070 | 37 | 37_pre | MEL | BASELINE | anti-PD1 | MR | 0.20 |
P3437_JMB_071 | 38 | 38_pre | MEL | BASELINE | anti-PD1 | MR | 0.50 |
P3437_JMB_072 | 39 | 39_pre | MEL | BASELINE | anti-PD1 | PR | 0.00 |
P3437_JMB_073 | 40 | 40_pre | MEL | BASELINE | anti-PD1 | CR | 0.75 |
P3437_JMB_074 | 5 | 5_post | MEL | PROGRESSION | anti-PD1 | RELAPSE | 0.00 |
P3437_JMB_075 | 41 | 41_pre | MEL | BASELINE | anti-PD1 | PD | 0.00 |
P3437_JMB_077 | 42 | 42_pre | MEL | BASELINE | anti-PD1 | CR | 0.10 |
P3437_JMB_078 | 43 | 43_pre | MEL | BASELINE | anti-PD1 | CR | 0.25 |
P3437_JMB_079 | 44 | 44_pre | MEL | BASELINE | anti-PD1 | PR | 0.00 |
P3437_JMB_008 | 45 | 45_pre | LUNG | BASELINE | anti-PD1 | PR | 0.00 |
P3437_JMB_083 | 6 | 6_post | LUNG | PROGRESSION | anti-PD1 | RELAPSE | NA |
P3437_JMB_084 | 46 | 46_pre | MEL | BASELINE | anti-PD1 | PD | NA |
P3437_JMB_085 | 47 | 47_pre | MEL | BASELINE | anti-PD1 | PD | NA |
P3437_JMB_088 | 48 | 48_pre | MEL | BASELINE | anti-PD1 | CR | NA |
P3437_JMB_009 | 49 | 49_pre | LUNG | BASELINE | anti-PD1 | SD | 0.00 |
P3437_JMB_090 | 50 | 50_pre | MEL | BASELINE | anti-PD1 | MR | NA |
P3437_JMB_093 | 51 | 51_pre | MEL | BASELINE | anti-PD1 | PD | NA |
P3437_JMB_095 | 52 | 52_pre | MEL | BASELINE | anti-PD1 | CR | NA |
P3437_JMB_096 | 53 | 53_pre | MEL | BASELINE | anti-PD1 | MR | NA |
Data are available on reasonable request by sending email to Justin M. Balko or Yaomin Xu.
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Zlatko Trajanoski; Francesca Finotello; Clemens Mayer; Christina Plattner; Gerhard Laschober; Dietmar Rieder; Hubert Hackl; Anne Krogsdam; Zuzana Loncova; Wilfried Posch; Doris Wilflingseder; Sieghart Sopper; Marieke Ijsselsteijn; Douglas Johnson; Yaomin Xu; Yu Wang; Melinda E. Sanders; Monica V. Estrada; Paula Ericsson-Gonzalez; Pornpimol Charoentong; Justin Balko; Noel de Miranda; Thomas P Brouwer. Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data. Genome Medicine. 2019 May 24;11(1):34. doi: 10.1186/s13073-019-0638-6, PubMed PMID: 31126321; PubMed Central PMCID: PMC6534875.