JPWO2021028726A5

JPWO2021028726A5 -

Info

Publication number: JPWO2021028726A5
Application number: JP2022500543A
Authority: JP
Publication date: 2023-07-19

Claims

a method,
obtaining a first biological sample of a first tumor, said first biological sample previously obtained from a subject having, suspected of having, or at risk of having cancer; , step and
extracting RNA from said first biological sample of said first tumor to obtain extracted RNA;
enriching the extracted RNA with respect to coding RNA to obtain enriched RNA;
sequencing the enriched RNA using at least one sequencing platform to obtain RNA expression data comprising at least 5 kilobases (kb);
using at least one hardware processor,
obtaining said RNA expression data using said at least one sequencing platform;
converting the RNA expression data into gene expression data;
determining bias-corrected gene expression data from said gene expression data, at least in part from said gene expression data by removing expression data for at least one gene that introduces a bias into said gene expression data;
using the bias-corrected gene expression data to generate information indicative of cancer treatment for the subject.

2. The method of claim 1 , wherein enriching the RNA for coding RNA comprises performing poly-A enrichment.

said at least one gene that introduces a bias into said gene expression data,
genes with average transcript lengths that are longer or shorter than the average length of transcripts in said gene expression data;
genes with at least one threshold variation in mean transcript expression level based on transcript expression levels in the reference sample;
and/or a gene having a polyA tail length that is at least a threshold amount less than the average polyA tail length of genes from the first biological sample for which said RNA expression data was obtained and/or the reference sample. 3. A method according to any one of claims 1 or 2 comprising.

The at least one gene that introduces a bias into the gene expression data is selected from the group consisting of histone-encoding genes, mitochondrial genes, interleukin-encoding genes, collagen-encoding genes, B-cell receptor-encoding genes, and T-cell receptor-encoding genes. 4. A method according to any one of claims 1 to 3, belonging to a family of genes that have been identified.

The at least one gene is HIST1H1A, HIST1H1B, HIST1H1C, HIST1H1D, HIST1H1E, HIST1H1T, HIST1H2AA, HIST1H2AB, HIST1H2AC, HIST1H2AD, HIST1H2AE, HIST1H2AG, HIST1H2AH, HIST1H2 AI, HIST1H2AJ, HIST1H2AK, HIST1H2AL, HIST1H2AM, HIST1H2BA, HIST1H2BB, HIST1H2BC, HIST1H2BD , HIST1H2BE, HIST1H2BF, HIST1H2BG, HIST1H2BH, HIST1H2BI, HIST1H2BJ, HIST1H2BK, HIST1H2BL, HIST1H2BM, HIST1H2BN, HIST1H2BO, HIST1H3A, HIST1H3B, HIST1H3 C, HIST1H3D, HIST1H3E, HIST1H3F, HIST1H3G, HIST1H3H, HIST1H3I, HIST1H3J, HIST1H4A, HIST1H4B, HIST1H4C, HIST1H4D , HIST1H4E, HIST1H4F, HIST1H4G, HIST1H4H, HIST1H4I, HIST1H4J, HIST1H4K, HIST1H4L, HIST2H2AA3, HIST2H2AA4, HIST2H2AB, HIST2H2AC, HIST2H2BE, HIST2H2BF, H From IST2H3A, HIST2H3C, HIST2H3D, HIST2H3PS2, HIST2H4A, HIST2H4B, HIST3H2A, HIST3H2BB, HIST3H3, and HIST4H4 at least one histone-encoding gene selected from the group of
said at least one gene is MT-ATP6, MT-ATP8, MT-CO1, MT-CO2, MT-CO3, MT-CYB, MT-ND1, MT-ND2, MT-ND3, MT-ND4, MT-ND4L , MT-ND5, MT-ND6, MT-RNR1, MT-RNR2, MT-TA, MT-TC, MT-TD, MT-TE, MT-TF, MT-TG, MT-TH, MT-TI, MT -TK, MT-TL1, MT-TL2, MT-TM, MT-TN, MT-TP, MT-TQ, MT-TR, MT-TS1, MT-TS2, MT-TT, MT-TV, MT-TW , MT-TY, MTRNR2L1, MTRNR2L10, MTRNR2L11, MTRNR2L12, MTRNR2L13, MTRNR2L3 , MTRNR2L4, MTRNR2L5, MTRNR2L6, MTRNR2L7, and MTRNR2L8. either The method according to item 1.

Determining the bias-corrected gene expression data comprises:
6. The method of any one of claims 1-5 , further comprising renormalizing the gene expression data after removing the expression data for the at least one gene that introduces a bias into the gene expression data.

Converting the RNA expression data to gene expression data comprises:
removing non-coding transcripts from the RNA expression data to obtain filtered RNA expression data;
normalizing the filtered RNA expression data after removing the non-coding transcripts to obtain Transcripts Per Million (TPM) gene expression data ;
The step of removing the non-coding transcripts from the RNA expression data comprises pseudogenes, polymorphic pseudogenes, process pseudogenes, transcribed process pseudogenes, unitary pseudogenes, non-process pseudogenes, transcribed unitary pseudogenes. genes, constant chain immunoglobulin (IG C) pseudogene, binding chain immunoglobulin (IG J) pseudogene, variable chain immunoglobulin (IG V) gene, transcribed non-processed gene, translated non-processed gene, binding chain T cell receptor (TR J) gene, variable chain T cell receptor (TR V) gene, small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), microRNA (miRNA), ribozyme , ribosomal RNA (rRNA), mitochondrial tRNA (Mt tRNA), mitochondrial rRNA (Mt rRNA), Cajal body-specific RNA (scaRNA), residual intron, sense intron RNA, sense overlapping RNA, nonsense mutation-dependent degradable RNA, nonstop degraded RNA, antisense RNA, long intervening noncoding RNA (lincRNA), macrolong noncoding RNA (macrolncRNA), processed transcript, 3' overlapping noncoding RNA (3' overlapping ncrna), small RNA (sRNA) , miscRNA, vaultRNA, and TEC RNA. .

Before removing said non-coding transcripts,
aligning the RNA expression data to a reference;
8. The method of claim 7 , further comprising annotating said RNA expression data.

said RNA expression data comprises at least 25 million paired-end reads; optionally,
9. The method of any one of claims 1-8 , wherein said RNA expression data comprises at least 50 million paired-end reads and has an average read length of at least 100 bp.

generating information indicative of the cancer treatment for the subject using the bias-corrected gene expression data,
determining a plurality of gene cluster expression levels using the bias-corrected gene expression data, wherein the plurality of gene cluster expression levels is a gene cluster expression level for each gene cluster in a set of gene clusters; wherein the set of genes includes at least one gene cluster associated with cancer malignancy and at least one gene cluster associated with cancer microenvironment;
and using the determined gene cluster expression levels to generate information indicative of the cancer treatment.

11. The method of any one of claims 1-10, wherein said cancer therapy is selected from the group consisting of radiation therapy, surgical therapy, chemotherapy and immunotherapy.

further comprising obtaining a second biological sample of a second tumor, wherein the second biological sample was previously obtained from the subject;
The method according to any one of claims 1 to 11, optionally comprising
further comprising combining the first biological sample and the second biological sample to form a combined tumor sample;
extracting the RNA comprises extracting the RNA from the combined tumor sample; and/or
extracting RNA from the second biological sample;
combining the RNA extracted from the second biological sample with the RNA extracted from the first biological sample to form a combined extracted RNA;
enriching the RNA for coding RNA comprises enriching the combined extracted RNA for coding RNA;
12. A method according to any one of claims 1-11 .

the extracted RNA comprises at least 1 μg of RNA after RNA extraction;
Optionally, the extracted RNA has a total mass of at least 1000-6000 ng and a purity corresponding to a ratio of absorbance at 260 nm to absorbance at 280 nm of at least 2.0 . The method according to item 1.

performing a quality control assessment on said RNA expression data, at least in part by :
obtaining claimed information indicative of the claimed source and/or claimed integrity of said RNA expression data;
processing the RNA expression data to obtain determined information indicative of the determined source and/or the determined integrity of the RNA expression data;
by determining whether the determined information matches the claimed information ;
Optionally, processing said RNA expression data comprises processing said RNA expression data to identify tissue type of said first biological sample, tumor type of said first biological sample, and/or guanine (G) and/or determining the percentage (%) of cytosine (C).

15. A system for carrying out the method of any one of claims 1 to 14 , said system comprising:
at least one sequencing platform configured to generate gene expression data from enriched RNA obtained from a first biological sample previously obtained from the subject, wherein the enriched RNA comprises (i) extracting RNA from said first biological sample of a first tumor to obtain extracted RNA; and (ii) enriching said extracted RNA for coding RNA to obtain enriched RNA. at least one sequencing platform obtained by and, wherein the RNA expression data comprises at least 5 kilobases (kb);
at least one computer hardware processor;
at least one non-transitory computer-readable storage medium storing processor-executable instructions, said processor-executable instructions, when executed by said at least one computer hardware processor; to the
obtaining said RNA expression data using said at least one sequencing platform;
converting the RNA expression data into gene expression data;
determining bias-corrected gene expression data from said gene expression data, at least in part from said gene expression data by removing expression data for at least one gene that introduces a bias into said gene expression data;
and generating information indicative of cancer treatment for said subject using said bias-corrected gene expression data.

A system for carrying out the method of any one of claims 1 to 14 , said system comprising at least one computer hardware processor;
at least one non-transitory computer-readable storage medium storing processor-executable instructions, said processor-executable instructions, when executed by said at least one computer hardware processor; to the
obtaining RNA expression data from at least one sequencing platform, wherein the RNA expression data comprises at least five kilobases (5 kb), the RNA expression data is the first sequence previously obtained from the subject; from a first biological sample of a tumor, at least in part: (i) extracting RNA from said first biological sample of said first tumor to obtain extracted RNA; concentrating the extracted RNA to obtain enriched RNA;
converting the RNA expression data into gene expression data;
determining bias-corrected gene expression data from said gene expression data, at least in part from said gene expression data by removing expression data for at least one gene that introduces a bias into said gene expression data;
and generating information indicative of cancer treatment for said subject using said bias-corrected gene expression data.

17. The system of Claim 16 , further comprising said at least one sequencing platform.

at least one non-transitory computer-readable storage medium storing processor-executable instructions, said processor-executable instructions, when executed by said at least one computer hardware processor; to the
obtaining RNA expression data from at least one sequencing platform, wherein said RNA expression data comprises at least five kilobases (5 kb), said RNA expression data having cancer, suspected of having cancer; or from a first biological sample of a first tumor previously obtained from a subject at risk of having cancer, at least in part (i) extracting RNA from said first biological sample of said first tumor; and (ii) enriching said extracted RNA with respect to coding RNA to obtain enriched RNA; and converting said RNA expression data into gene expression data. and
determining bias-corrected gene expression data from said gene expression data, at least in part from said gene expression data by removing expression data for at least one gene that introduces a bias into said gene expression data;
using the bias-corrected gene expression data to generate information indicative of cancer therapy for the subject. Temporary computer-readable storage medium.