Table 2.

Multi-omics-based MRD monitoring and treatment response surveillance.

MRD monitoring based on multi-omics data
Cancer type	Cohort design	Follow-up	Blood collection	Detection methods	Control	Target features	Main outcome and measures	Setting (ctDNA monitoring)	Major conclusions	Ref.
Hepatocellular carcinoma	34 patients	Long term	At preoperative, postoperative, and multiple follow-up time points	Targeted sequencing, low-coverage whole-genome sequencing, and protein quantification	Tumour-informed	ctDNA somatic mutation and Des-Gamma CarboxyProthrombin (DCP)	RFS, OS	Adjuvant	Integrative analysis of ctDNA mutations and DCP enabled a better evaluation of patients' prognostic risk and tumour occurrence detection prior to traditional strategies	[98]
Triple-negative breast cancer	196 patients	Median of 17.2 months	At the time of treatment assignment	Targeted sequencing (62–70 cancer-related genes + 7–6 genes frequently rearranged in cancer) and CTC enumeration	Tumour-informed	ctDNA somatic mutation and CTC	DDFS, DFS, and OS	Neoadjuvant	Detection of ctDNA and CTCs in patients with early-stage triple-negative breast cancer after neoadjuvant chemotherapy could be an important stratification factor	[99]
Leiomyosarcoma	7 patients and 24 healthy controls	Long term	At follow-up time points of post-treatment	CAPP-seq and GRP	Tumour-informed	Single-nucleotide variants, small indels, and copy-number alterations in ctDNA	OS	Surgery or chemotherapy	Joint analysis of SNVs, indels, and genome- wide CNAs could allow the comprehensive monitoring of tumour-specific markers in plasma for leiomyosarcoma	[100]
Colorectal cancer	103 patients	Up to 1 year	1 month after definitive therapy	Targeted sequencing (500 kb panel)	Tumour-naive	ctDNA somatic mutation and methylation	RFS	Surgery only or surgery with neoaduvant/adjuvant therapy	Plasma-only MRD detection based on integrative analysis of epigenomic and genomic alterations could achieve comparable performance to tumour-informed approaches	[101]
Head and neck squamous cell carcinoma	30 patients and 20 risk-matched healthy controls	Minimum 2 years	At diagnosis and at least one timepoint post- treatment	CAPP-seq and cfMeDIP-seq	Tumour-naive	ctDNA somatic mutation and methylation	OS	Surgery only or surgery with adjuvant therapy	Tumour-navie detection of ctDNA through multimodal profiling of mutation and methylation could facilitate corresponding biomarker discovery and clinical use	[102]

Treatment response surveillance based on multi-omics data
Cancer type	Treatment methods	Cohort design	Follow-up	Blood collection	Detection methods	Target features		Major conclusions		Ref
Non-small cell lung cancer	Treated with immune checkpoint inhibitors (ICIs)	99 patients	Monitoring at least 6 months after treatment with PD-(L)1 blockade-based ICI	Before treatment, and after initiation of therapy with median of 18.5 days	RNA-seq, CAPP-Seq, WES and flow cytometry	ctDNA, PD-L1 expression, circulating CD8 T cell and bTMB		Integrative analysis of ctDNA and circulating immune cells in plasma could enable accurate and early forecasting of ultimate outcomes for NSCLC patients receiving immune checkpoint inhibitors		[120]
Non-small cell lung cancer	Treated with immune checkpoint blockade	24 metastatic patients and 14 early stage patients	Median duration of follow-up was 12.7 months and 16 months for metastatic and early stage patients, respectively.	At least 2 serial blood samples (range 2–8) over the course of treatment	TEC-Seq and TCR clonal expansion analysis	ctDNA and TCR dynamics		The combination of ctDNA and TCR repertoire was useful for the rapid determination of treatment outcomes for NSCLC patients treated with immune checkpoint inhibitors		[121]
Metastatic breast cancers	Treated with endocrine therapy	45 patients	Monitored at least 6 months	−28 to −1 days prior to treatment initiation, on the day of treatment initiation, 4 weeks for the first six cycles and 6 weeks thereafter	ddPCR and CTC enumeration	ctDNA ESR1LBDm and CTC		Joint analysis of ctDNA and CTC could improve outcome prediction and mechanism identification of therapy resistance than using a single biomarker for metastatic breast cancers		[122]
Locally advanced or metastatic pancreatic cancer	With first-line treatment	100 patients	Median of 7.7 months	Before initiation of chemotherapy and after the first cycle of chemotherapy	DNA chip and cfDNA fragment size analysis	cfDNA level and cfDNA fragment		They demonstrated that cfDNA fragment size and cfDNA levels were useful for predicting the clinical outcome in patients with advanced pancreatic cancer		[119]
Metastatic colorectal cancer	Treated in first- or second- line chemotherapy	82 patients	Long term	Before the first cycle, before the second and/or third cycle of chemotherapy	Picodroplet digital PCR	ctDNA gene mutations (KRAS, BRAF, TP53) or hypermethylation (WIFI, NPY) based ctDNA concentration		Early change in ctDNA concentration inferred from tumour-specific genetic or epigenetic alterations could predict the therapeutic efficacy in patients with metastatic colorectal cancer		[117]

CAPP-seq cancer personalised profiling by deep sequencing, GRP genome representation profiling, cfMeDIP-seq cell-free methylated DNA immuno-precipitation and high-throughput sequencing, OS overall survival, RFS recurrence-free survival, DDFS distant disease-free survival, DFS disease-free survival, ICI immune checkpoint inhibitor, CTC circulating tumour cell, TEC-Seq targeted error-correction sequencing, TCR T cell receptor, ddPCR droplet digital PCR, NSCLC non-small cell lung cancer.